Actowiz Metrics Real-time
logo
analytics dashboard for brands! Try Free Demo
How to Maximize ROI with Customizable E-commerce Dashboards

Introduction

India’s real estate and housing sector has witnessed tremendous growth over the last decade, driven by urbanization, infrastructure development, and rising demand. However, this expansion also brought challenges like project delays, miscommunication, and regulatory loopholes. To address these, the government introduced the Real Estate (Regulation and Development) Act (RERA), bringing much-needed transparency and accountability to the industry. With thousands of projects and developers registered across state-level RERA portals, a vast amount of valuable data is now available—but it’s often scattered and difficult to compile manually. This is where RERA Data Scraping India becomes a game-changer. By automating the extraction of project approvals, completion statuses, and builder histories, businesses can unlock deep insights. Whether you're a builder, analyst, or investor, property market data scraping India and real estate and housing data scraping enable smarter decisions, improved compliance, and competitive advantage in today’s rapidly evolving property landscape.

What is RERA and Why It Matters?

What-is-RERA-Data-Extraction-

The Real Estate (Regulation and Development) Act, commonly known as RERA, was enacted in 2016 to bring about a transformative shift in India’s real estate ecosystem. The primary purpose of this landmark legislation is to protect homebuyers, enhance transparency, ensure timely delivery of projects, and create a more accountable system for developers and agents. Before RERA, property buyers faced rampant issues like project delays, hidden charges, and poor grievance redressal. Now, with mandatory disclosures on RERA portals, the entire real estate sector is more regulated and data-rich.

Every state in India has its own RERA portal where developers must register projects, disclose timelines, update construction progress, and provide details of approvals. This has created a goldmine of publicly available information, including project registrations, current status, approvals, agent records, builder profiles, legal disputes, and complaints. Leveraging this data manually, however, is time-consuming and inconsistent.

That’s where automated web scraping services come into play. Using advanced builder data scraping services, businesses can extract real-time data from RERA portals to monitor compliance, evaluate competitors, and assess market trends. This data is essential for developers, investors, consultants, and government agencies seeking accurate insights.

By using real estate compliance data extraction tools, stakeholders can track how well builders are adhering to approved timelines and regulations. Additionally, real estate data intelligence services help transform raw RERA data into actionable insights—such as identifying trustworthy developers, forecasting project completion, or spotting regulatory bottlenecks.

In a fast-moving and data-dependent industry, RERA provides the foundation for a more transparent marketplace. Extracting and analyzing this data through specialized scraping tools empowers businesses with the knowledge needed to reduce risks and make informed, confident decisions.

What is RERA Data Scraping?

What-is-RERA-Data-Extraction-

RERA Data Scraping refers to the process of extracting publicly available data from state-level RERA (Real Estate Regulatory Authority) portals using automated tools or scripts. These portals host a wide range of information about real estate projects, including project registration details, construction progress updates, builder profiles, regulatory approvals, agent registrations, and legal complaints. Through automated real estate data extraction, this valuable data can be compiled, structured, and analyzed at scale, providing crucial Indian property market insights for various stakeholders.

The types of data typically scraped from RERA portals include:

  • Project registration number and developer name
  • Project start and end dates
  • Location, configuration, and carpet area details
  • Current construction status and completion stages
  • Builder history and compliance status
  • Agent registration and contact information
  • Regulatory approvals and related documents
  • Complaints filed and their resolutions

Real-time property data scraping enables developers, investors, consultants, and analysts to access continuously updated information without manually navigating multiple state portals. This improves decision-making, supports compliance checks, and strengthens risk analysis. For example, a real estate investor can assess builder credibility by tracking delays or complaint records across several projects.

From a legal and ethical standpoint, RERA data scraping must comply with public data usage norms. Since the data is already made publicly accessible under the RERA Act to promote transparency, scraping it—when done responsibly—does not violate any privacy laws. However, it's critical to follow best practices like rate-limiting requests, avoiding data misuse, and maintaining data accuracy.

By leveraging automated real estate data extraction, companies gain a powerful edge in accessing structured datasets, enabling them to unlock deep Indian property market insights and maintain a competitive advantage in the fast-evolving real estate landscape.

Unlock powerful insights with RERA Data Scraping India—automate real-time data extraction to stay ahead in the dynamic Indian property market.
Get started today!

Benefits of RERA Data Scraping for Builders

What-is-RERA-Data-Extraction-
Monitor Competitor Projects and Timelines

With RERA Data Scraping India, builders can track competitor activities across various regions. From project registration to completion status, every step is logged on RERA portals. This data allows builders to benchmark timelines, identify construction trends, and adjust their go-to-market strategies accordingly using property market data scraping India tools.

Stay Compliant with Regulatory Updates

Staying updated with compliance requirements is crucial for any developer. Through real estate and housing data scraping, builders can automate the tracking of project approval status, deadlines, and new regulations published on RERA sites. This ensures that no important compliance update is missed, reducing legal risks and enhancing builder reputation.

Streamline Planning and Reduce Development Risks

Access to historical and real-time RERA data helps builders anticipate delays, spot regulatory hurdles, and prepare for challenges. By using RERA data scraping India, they can streamline the planning process, allocate resources better, and avoid costly project overruns. This makes development more efficient and less risky.

Access Pricing Intelligence and Demand Insights

Builders can use property market data scraping India solutions to study price trends across different regions and property types. This allows them to make smarter decisions on pricing, identify high-demand areas, and tailor offerings based on actual market needs. The result is optimized profitability and improved project success rates.

Advantages for Real Estate Analysts

What-is-RERA-Data-Extraction-
Perform Market Trend Analysis

Real estate analysts rely heavily on data to detect emerging trends and shifts in buyer behavior. By leveraging web scraping services to collect data from RERA portals, analysts can study region-wise launches, pricing patterns, construction timelines, and delivery performance. These insights help in creating accurate forecasts and identifying investment-worthy markets.

Evaluate Developer Track Records and Credibility

With access to structured data through builder data scraping services, analysts can review the historical performance of developers. By analyzing factors like project delays, litigation records, complaint resolutions, and approval statuses, they can measure a builder’s credibility and risk profile. This evaluation is vital for investors, banks, and consultants before recommending or funding a project.

Analyze Delays, Cancellations, and Dispute Patterns

Using real estate compliance data extraction, analysts can track instances of project delays, cancellations, and regulatory disputes. This information helps in understanding which projects or developers are consistent performers and which are risky. Such analysis can support strategic decisions on acquisitions, partnerships, or portfolio adjustments.

Create Real-Time Investment or Project Feasibility Reports

Through automated real estate data intelligence services, analysts can convert raw RERA data into actionable reports and dashboards. These include feasibility studies, ROI projections, and risk assessments, based on real-time data feeds. This enables quicker decision-making for clients and adds credibility to their advisory work.

By combining web scraping services with builder data scraping services, real estate analysts gain a holistic view of the market. The ability to extract, process, and interpret data at scale enables smarter, faster, and more accurate decision-making in India’s dynamic real estate landscape.

How RERA Data Scraping India Improves Decision-Making?

What-is-RERA-Data-Extraction-

RERA Data Scraping India plays a pivotal role in strengthening data-driven strategies for developers, investors, consultants, and market researchers. By integrating automated real estate data extraction with internal systems, stakeholders can make more informed decisions and minimize risks in a highly competitive environment.

Fuel Dashboards and Analytics Platforms with Real-Time RERA Data

Using real-time property data scraping, organizations can populate dashboards with the latest updates on project approvals, launch timelines, builder histories, and compliance metrics. This enables dynamic tracking of project portfolios, regional growth patterns, and emerging opportunities across multiple states.

Drive Strategic Decisions Using Enriched Data Streams

When decision-makers have access to structured and enriched datasets through automated real estate data extraction, they can identify gaps in the market, assess competition more accurately, and prioritize high-yield investments. RERA Data Scraping India ensures that decisions are based on factual, real-time information instead of outdated reports or manual research.

Practical Use Cases: Location Scouting, Investor Presentations, Price Benchmarking

Builders and consultants can leverage Indian property market insights to scout the most promising locations for upcoming projects by analyzing data like nearby project saturation, average delivery timelines, and pricing bands. In investor presentations, showcasing detailed RERA-backed analytics adds credibility and transparency. Additionally, real-time property data scraping allows for accurate price benchmarking, enabling competitive and profitable pricing strategies.

Overall, RERA Data Scraping India bridges the gap between raw government data and strategic decision-making. By transforming scattered information into digestible, actionable insights, it empowers stakeholders to stay ahead of the curve, identify trends early, and make smarter choices in the ever-evolving Indian property market.

Boost your strategy with RERA Data Scraping India—access real-time property data for smarter decisions, precise pricing, and winning investments.
Start leveraging data now!

Challenges in RERA Data Scraping

What-is-RERA-Data-Extraction-

While RERA Data Scraping India offers immense benefits, several challenges can complicate the extraction of accurate and timely data from various RERA portals. Understanding these obstacles is key for builders, analysts, and data service providers working in the real estate domain.

Disparity in Data Structure Across Different State Portals

India’s real estate market is regulated by multiple state-level RERA authorities, each maintaining its own portal. Unfortunately, the data formats, page layouts, and information categorization vary widely. This lack of standardization makes real estate and housing data scraping complex, requiring customized scraping solutions for each state to extract consistent and comparable data.

CAPTCHA Restrictions and Anti-Scraping Mechanisms

Many RERA websites implement security measures like CAPTCHAs, IP blocking, and request throttling to prevent automated access. These anti-scraping mechanisms pose significant hurdles for property market data scraping India initiatives, as they can interrupt data collection, slow down extraction speed, or lead to incomplete datasets. Overcoming these requires advanced techniques like proxy rotation, human-like interaction simulation, or OCR-based CAPTCHA solving.

Frequent Updates Needed to Maintain Data Accuracy and Quality

RERA data is continuously updated, with new project registrations, status changes, and complaint resolutions occurring daily. To ensure relevance, RERA Data Scraping India must be a recurring process rather than a one-time extraction. Maintaining high data accuracy demands regular crawling, validation, and synchronization with live portals, which can be resource-intensive and technically challenging.

Despite these challenges, leveraging professional real estate and housing data scraping services with expertise in handling such complexities can deliver reliable, high-quality data. This empowers stakeholders to make confident decisions based on the most up-to-date insights available in the property market data scraping India ecosystem.

How Actowiz Solutions Can Help?

Actowiz Solutions offers customized RERA Data Scraping India services that provide structured data from multiple state RERA portals, empowering builders, brokers, and analysts. Our advanced scraping technology overcomes challenges like CAPTCHAs and anti-scraping blocks with scalable, automated solutions. We deliver real-time data feeds to keep you updated on the latest project statuses and compliance information. Our intuitive data visualization and dashboards turn complex RERA data into actionable insights. We prioritize compliance first, ensuring ethically sourced data aligned with legal standards. Partner with our experts for tailored consultation and solutions that meet your exact Indian property market insights needs.

Conclusion

RERA Data Scraping India empowers developers and analysts by providing accurate, real-time insights essential for navigating India’s dynamic property market. In a sector where timely information can make or break projects, access to structured, up-to-date data enhances compliance, risk management, and strategic planning. As the Indian real estate landscape evolves rapidly, the demand for reliable real estate and housing data scraping grows stronger. With advanced tools and expert support from providers like Actowiz Solutions, stakeholders can unlock deep Indian property market insights and maintain a significant competitive edge well into 2025 and beyond. Looking to harness the power of RERA Data Scraping India? Get in touch with Actowiz Solutions today for a demo or a custom data solution to transform your real estate intelligence. You can also reach us for all your mobile app scraping, data collection, web scraping , and instant data scraper service requirements!

Social Proof That Converts

Trusted by Global Leaders Across Q-Commerce, Travel, Retail, and FoodTech

Our web scraping expertise is relied on by 3,000+ global enterprises including Zomato, Tata Consumer, Subway, and Expedia — helping them turn web data into growth.

3,000+ Enterprises Worldwide
50+ Countries Served
20+ Industries
Join 3,000+ companies growing with Actowiz →
Real Results from Real Clients

Hear It Directly from Our Clients

Watch how businesses like yours are using Actowiz data to drive growth.

1 min
★★★★★
"Actowiz Solutions offered exceptional support with transparency and guidance throughout. Anna and Saga made the process easy for a non-technical user like me. Great service, fair pricing!"
FC
Febbin Chacko
Small Business Owner
Fin
2 min
★★★★★
"Actowiz delivered impeccable results for our company. Their team ensured data accuracy and on-time delivery. The competitive intelligence completely transformed our pricing strategy."
JI
Javier Ibanez
Head of Analytics
atacy.es
1:30
★★★★★
"What impressed me most was the speed — we went from requirement to production data in under 48 hours. The API integration was seamless and the support team is always responsive."
RK
Rajesh Kumar
CTO
QComm Brand
4.8/5 Average Rating
📹 50+ Video Testimonials
🔄 92% Client Retention
🌍 50+ Countries Served

Join 3,000+ Companies Growing with Actowiz

From Zomato to Expedia — see why global leaders trust us with their data.

Why Global Leaders Trust Actowiz

Backed by automation, data volume, and enterprise-grade scale — we help businesses from startups to Fortune 500s extract competitive insights across the USA, UK, UAE, and beyond.

icons
7+
Years of Experience
Proven track record delivering enterprise-grade web scraping and data intelligence solutions.
icons
4,000+
Projects Delivered
Serving startups to Fortune 500 companies across 50+ countries worldwide.
icons
200+
In-House Experts
Dedicated engineers across scrapers, AI/ML models, APIs, and data quality assurance.
icons
9.2M
Automated Workflows
Running weekly across eCommerce, Quick Commerce, Travel, Real Estate, and Food industries.
icons
270+ TB
Data Transferred
Real-time and batch data scraping at massive scale, across industries globally.
icons
380M+
Pages Crawled Weekly
Scaled infrastructure for comprehensive global data coverage with 99% accuracy.

AI Solutions Engineered
for Your Needs

LLM-Powered Attribute Extraction: High-precision product matching using large language models for accurate data classification.
Advanced Computer Vision: Fine-grained object detection for precise product classification using text and image embeddings.
GPT-Based Analytics Layer: Natural language query-based reporting and visualization for business intelligence.
Human-in-the-Loop AI: Continuous feedback loop to improve AI model accuracy over time.
🎯 Product Matching 🏷️ Attribute Tagging 📝 Content Optimization 💬 Sentiment Analysis 📊 Prompt-Based Reporting

Connect the Dots Across
Your Retail Ecosystem

We partner with agencies, system integrators, and technology platforms to deliver end-to-end solutions across the retail and digital shelf ecosystem.

icons
Analytics Services
icons
Ad Tech
icons
Price Optimization
icons
Business Consulting
icons
System Integration
icons
Market Research
Become a Partner →

Popular Datasets — Ready to Download

Browse All Datasets →
icons
Amazon
eCommerce
Free 100 rows
icons
Zillow
Real Estate
Free 100 rows
icons
DoorDash
Food Delivery
Free 100 rows
icons
Walmart
Retail
Free 100 rows
icons
Booking.com
Travel
Free 100 rows
icons
Indeed
Jobs
Free 100 rows

Latest Insights & Resources

View All Resources →
thumb
Blog

How IHG Hotels & Resorts Data Scraping Helps Overcome Real-Time Availability and Rate Monitoring Issues

How IHG Hotels & Resorts data scraping enables real-time rate tracking, improves availability monitoring, and boosts revenue decisions.

thumb
Case Study

UK Grocery Chain Achieves 300% ROI on Promotional Campaigns

How a top-10 UK grocery retailer used Actowiz grocery price scraping to achieve 300% promotional ROI and reduce competitive response time from 5 days to same-day.

thumb
Report

Track UK Grocery Products Daily Using Automated Data Scraping to Monitor 50,000+ UK Grocery Products from Morrisons, Asda, Tesco, Sainsbury’s, Iceland, Co-op, Waitrose, Ocado

Track UK Grocery Products Daily Using Automated Data Scraping across Morrisons, Asda, Tesco, Sainsbury’s, Iceland, Co-op, Waitrose, and Ocado for insights.

Start Where It Makes Sense for You

Whether you're a startup or a Fortune 500 — we have the right plan for your data needs.

icons
Enterprise
Book a Strategy Call
Custom solutions, dedicated support, volume pricing for large-scale needs.
icons
Growing Brand
Get Free Sample Data
Try before you buy — 500 rows of real data, delivered in 2 hours. No strings.
icons
Just Exploring
View Plans & Pricing
Transparent plans from $500/mo. Find the right fit for your budget and scale.
GeoIp2\Model\City Object
(
    [raw:protected] => Array
        (
            [city] => Array
                (
                    [geoname_id] => 4509177
                    [names] => Array
                        (
                            [de] => Columbus
                            [en] => Columbus
                            [es] => Columbus
                            [fr] => Columbus
                            [ja] => コロンバス
                            [pt-BR] => Columbus
                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
                        )

                )

            [continent] => Array
                (
                    [code] => NA
                    [geoname_id] => 6255149
                    [names] => Array
                        (
                            [de] => Nordamerika
                            [en] => North America
                            [es] => Norteamérica
                            [fr] => Amérique du Nord
                            [ja] => 北アメリカ
                            [pt-BR] => América do Norte
                            [ru] => Северная Америка
                            [zh-CN] => 北美洲
                        )

                )

            [country] => Array
                (
                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
                        (
                            [de] => USA
                            [en] => United States
                            [es] => Estados Unidos
                            [fr] => États Unis
                            [ja] => アメリカ
                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

                )

            [location] => Array
                (
                    [accuracy_radius] => 20
                    [latitude] => 39.9625
                    [longitude] => -83.0061
                    [metro_code] => 535
                    [time_zone] => America/New_York
                )

            [postal] => Array
                (
                    [code] => 43215
                )

            [registered_country] => Array
                (
                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
                        (
                            [de] => USA
                            [en] => United States
                            [es] => Estados Unidos
                            [fr] => États Unis
                            [ja] => アメリカ
                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

                )

            [subdivisions] => Array
                (
                    [0] => Array
                        (
                            [geoname_id] => 5165418
                            [iso_code] => OH
                            [names] => Array
                                (
                                    [de] => Ohio
                                    [en] => Ohio
                                    [es] => Ohio
                                    [fr] => Ohio
                                    [ja] => オハイオ州
                                    [pt-BR] => Ohio
                                    [ru] => Огайо
                                    [zh-CN] => 俄亥俄州
                                )

                        )

                )

            [traits] => Array
                (
                    [ip_address] => 216.73.216.153
                    [prefix_len] => 22
                )

        )

    [continent:protected] => GeoIp2\Record\Continent Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [code] => NA
                    [geoname_id] => 6255149
                    [names] => Array
                        (
                            [de] => Nordamerika
                            [en] => North America
                            [es] => Norteamérica
                            [fr] => Amérique du Nord
                            [ja] => 北アメリカ
                            [pt-BR] => América do Norte
                            [ru] => Северная Америка
                            [zh-CN] => 北美洲
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => code
                    [1] => geonameId
                    [2] => names
                )

        )

    [country:protected] => GeoIp2\Record\Country Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
                        (
                            [de] => USA
                            [en] => United States
                            [es] => Estados Unidos
                            [fr] => États Unis
                            [ja] => アメリカ
                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                )

        )

    [locales:protected] => Array
        (
            [0] => en
        )

    [maxmind:protected] => GeoIp2\Record\MaxMind Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                )

            [validAttributes:protected] => Array
                (
                    [0] => queriesRemaining
                )

        )

    [registeredCountry:protected] => GeoIp2\Record\Country Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
                        (
                            [de] => USA
                            [en] => United States
                            [es] => Estados Unidos
                            [fr] => États Unis
                            [ja] => アメリカ
                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                )

        )

    [representedCountry:protected] => GeoIp2\Record\RepresentedCountry Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                    [5] => type
                )

        )

    [traits:protected] => GeoIp2\Record\Traits Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [ip_address] => 216.73.216.153
                    [prefix_len] => 22
                    [network] => 216.73.216.0/22
                )

            [validAttributes:protected] => Array
                (
                    [0] => autonomousSystemNumber
                    [1] => autonomousSystemOrganization
                    [2] => connectionType
                    [3] => domain
                    [4] => ipAddress
                    [5] => isAnonymous
                    [6] => isAnonymousProxy
                    [7] => isAnonymousVpn
                    [8] => isHostingProvider
                    [9] => isLegitimateProxy
                    [10] => isp
                    [11] => isPublicProxy
                    [12] => isResidentialProxy
                    [13] => isSatelliteProvider
                    [14] => isTorExitNode
                    [15] => mobileCountryCode
                    [16] => mobileNetworkCode
                    [17] => network
                    [18] => organization
                    [19] => staticIpScore
                    [20] => userCount
                    [21] => userType
                )

        )

    [city:protected] => GeoIp2\Record\City Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [geoname_id] => 4509177
                    [names] => Array
                        (
                            [de] => Columbus
                            [en] => Columbus
                            [es] => Columbus
                            [fr] => Columbus
                            [ja] => コロンバス
                            [pt-BR] => Columbus
                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => names
                )

        )

    [location:protected] => GeoIp2\Record\Location Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [accuracy_radius] => 20
                    [latitude] => 39.9625
                    [longitude] => -83.0061
                    [metro_code] => 535
                    [time_zone] => America/New_York
                )

            [validAttributes:protected] => Array
                (
                    [0] => averageIncome
                    [1] => accuracyRadius
                    [2] => latitude
                    [3] => longitude
                    [4] => metroCode
                    [5] => populationDensity
                    [6] => postalCode
                    [7] => postalConfidence
                    [8] => timeZone
                )

        )

    [postal:protected] => GeoIp2\Record\Postal Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [code] => 43215
                )

            [validAttributes:protected] => Array
                (
                    [0] => code
                    [1] => confidence
                )

        )

    [subdivisions:protected] => Array
        (
            [0] => GeoIp2\Record\Subdivision Object
                (
                    [record:GeoIp2\Record\AbstractRecord:private] => Array
                        (
                            [geoname_id] => 5165418
                            [iso_code] => OH
                            [names] => Array
                                (
                                    [de] => Ohio
                                    [en] => Ohio
                                    [es] => Ohio
                                    [fr] => Ohio
                                    [ja] => オハイオ州
                                    [pt-BR] => Ohio
                                    [ru] => Огайо
                                    [zh-CN] => 俄亥俄州
                                )

                        )

                    [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                        (
                            [0] => en
                        )

                    [validAttributes:protected] => Array
                        (
                            [0] => confidence
                            [1] => geonameId
                            [2] => isoCode
                            [3] => names
                        )

                )

        )

)
 country : United States
 city : Columbus
US
Array
(
    [as_domain] => amazon.com
    [as_name] => Amazon.com, Inc.
    [asn] => AS16509
    [continent] => North America
    [continent_code] => NA
    [country] => United States
    [country_code] => US
)
Array
(
    [city] => Columbus
    [country] => United States
    [countryCode] => +1
    [currencyCode] => USD
)
Get in Touch
Let's Talk About
Your Data Needs
Tell us what data you need — we'll scope it for free and share a sample within hours.
  • Free Sample in 2 HoursShare your requirement, get 500 rows of real data — no commitment.
  • 💰
    Plans from $500/monthFlexible pricing for startups, growing brands, and enterprises.
  • 🇺🇸
    US-Based SupportOffices in New York & California. Aligned with your timezone.
  • 🔒
    ISO 9001 & 27001 CertifiedEnterprise-grade security and quality standards.
Request Free Sample Data
Fill the form below — our team will reach out within 2 hours.
+1
Free 500-row sample · No credit card · Response within 2 hours
GeoIp2\Model\City Object
(
    [raw:protected] => Array
        (
            [city] => Array
                (
                    [geoname_id] => 4509177
                    [names] => Array
                        (
                            [de] => Columbus
                            [en] => Columbus
                            [es] => Columbus
                            [fr] => Columbus
                            [ja] => コロンバス
                            [pt-BR] => Columbus
                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
                        )

                )

            [continent] => Array
                (
                    [code] => NA
                    [geoname_id] => 6255149
                    [names] => Array
                        (
                            [de] => Nordamerika
                            [en] => North America
                            [es] => Norteamérica
                            [fr] => Amérique du Nord
                            [ja] => 北アメリカ
                            [pt-BR] => América do Norte
                            [ru] => Северная Америка
                            [zh-CN] => 北美洲
                        )

                )

            [country] => Array
                (
                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
                        (
                            [de] => USA
                            [en] => United States
                            [es] => Estados Unidos
                            [fr] => États Unis
                            [ja] => アメリカ
                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

                )

            [location] => Array
                (
                    [accuracy_radius] => 20
                    [latitude] => 39.9625
                    [longitude] => -83.0061
                    [metro_code] => 535
                    [time_zone] => America/New_York
                )

            [postal] => Array
                (
                    [code] => 43215
                )

            [registered_country] => Array
                (
                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
                        (
                            [de] => USA
                            [en] => United States
                            [es] => Estados Unidos
                            [fr] => États Unis
                            [ja] => アメリカ
                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

                )

            [subdivisions] => Array
                (
                    [0] => Array
                        (
                            [geoname_id] => 5165418
                            [iso_code] => OH
                            [names] => Array
                                (
                                    [de] => Ohio
                                    [en] => Ohio
                                    [es] => Ohio
                                    [fr] => Ohio
                                    [ja] => オハイオ州
                                    [pt-BR] => Ohio
                                    [ru] => Огайо
                                    [zh-CN] => 俄亥俄州
                                )

                        )

                )

            [traits] => Array
                (
                    [ip_address] => 216.73.216.153
                    [prefix_len] => 22
                )

        )

    [continent:protected] => GeoIp2\Record\Continent Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [code] => NA
                    [geoname_id] => 6255149
                    [names] => Array
                        (
                            [de] => Nordamerika
                            [en] => North America
                            [es] => Norteamérica
                            [fr] => Amérique du Nord
                            [ja] => 北アメリカ
                            [pt-BR] => América do Norte
                            [ru] => Северная Америка
                            [zh-CN] => 北美洲
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => code
                    [1] => geonameId
                    [2] => names
                )

        )

    [country:protected] => GeoIp2\Record\Country Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
                        (
                            [de] => USA
                            [en] => United States
                            [es] => Estados Unidos
                            [fr] => États Unis
                            [ja] => アメリカ
                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                )

        )

    [locales:protected] => Array
        (
            [0] => en
        )

    [maxmind:protected] => GeoIp2\Record\MaxMind Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                )

            [validAttributes:protected] => Array
                (
                    [0] => queriesRemaining
                )

        )

    [registeredCountry:protected] => GeoIp2\Record\Country Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
                        (
                            [de] => USA
                            [en] => United States
                            [es] => Estados Unidos
                            [fr] => États Unis
                            [ja] => アメリカ
                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                )

        )

    [representedCountry:protected] => GeoIp2\Record\RepresentedCountry Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                    [5] => type
                )

        )

    [traits:protected] => GeoIp2\Record\Traits Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [ip_address] => 216.73.216.153
                    [prefix_len] => 22
                    [network] => 216.73.216.0/22
                )

            [validAttributes:protected] => Array
                (
                    [0] => autonomousSystemNumber
                    [1] => autonomousSystemOrganization
                    [2] => connectionType
                    [3] => domain
                    [4] => ipAddress
                    [5] => isAnonymous
                    [6] => isAnonymousProxy
                    [7] => isAnonymousVpn
                    [8] => isHostingProvider
                    [9] => isLegitimateProxy
                    [10] => isp
                    [11] => isPublicProxy
                    [12] => isResidentialProxy
                    [13] => isSatelliteProvider
                    [14] => isTorExitNode
                    [15] => mobileCountryCode
                    [16] => mobileNetworkCode
                    [17] => network
                    [18] => organization
                    [19] => staticIpScore
                    [20] => userCount
                    [21] => userType
                )

        )

    [city:protected] => GeoIp2\Record\City Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [geoname_id] => 4509177
                    [names] => Array
                        (
                            [de] => Columbus
                            [en] => Columbus
                            [es] => Columbus
                            [fr] => Columbus
                            [ja] => コロンバス
                            [pt-BR] => Columbus
                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => names
                )

        )

    [location:protected] => GeoIp2\Record\Location Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [accuracy_radius] => 20
                    [latitude] => 39.9625
                    [longitude] => -83.0061
                    [metro_code] => 535
                    [time_zone] => America/New_York
                )

            [validAttributes:protected] => Array
                (
                    [0] => averageIncome
                    [1] => accuracyRadius
                    [2] => latitude
                    [3] => longitude
                    [4] => metroCode
                    [5] => populationDensity
                    [6] => postalCode
                    [7] => postalConfidence
                    [8] => timeZone
                )

        )

    [postal:protected] => GeoIp2\Record\Postal Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [code] => 43215
                )

            [validAttributes:protected] => Array
                (
                    [0] => code
                    [1] => confidence
                )

        )

    [subdivisions:protected] => Array
        (
            [0] => GeoIp2\Record\Subdivision Object
                (
                    [record:GeoIp2\Record\AbstractRecord:private] => Array
                        (
                            [geoname_id] => 5165418
                            [iso_code] => OH
                            [names] => Array
                                (
                                    [de] => Ohio
                                    [en] => Ohio
                                    [es] => Ohio
                                    [fr] => Ohio
                                    [ja] => オハイオ州
                                    [pt-BR] => Ohio
                                    [ru] => Огайо
                                    [zh-CN] => 俄亥俄州
                                )

                        )

                    [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                        (
                            [0] => en
                        )

                    [validAttributes:protected] => Array
                        (
                            [0] => confidence
                            [1] => geonameId
                            [2] => isoCode
                            [3] => names
                        )

                )

        )

)
 country : United States
 city : Columbus
US
Array
(
    [as_domain] => amazon.com
    [as_name] => Amazon.com, Inc.
    [asn] => AS16509
    [continent] => North America
    [continent_code] => NA
    [country] => United States
    [country_code] => US
)

Request Free Sample Data

Our team will reach out within 2 hours with 500 rows of real data — no credit card required.

+1
Free 500-row sample · No credit card · Response within 2 hours