Software Alternatives, Accelerators & Startups
Register | Login

Google BigQuery VS HasData

Compare Google BigQuery VS HasData and see what are their differences

boldrouter
A unified, OpenAI-compatible gateway to every major LLM provider. One endpoint, one key, one bill - with automatic routing and failover. sponsored
Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.
Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

Google BigQuery logo Google BigQuery

A fully managed data warehouse for large-scale data analytics.

HasData logo HasData

HasData is a top web scraping platform for developers and enterprises. It delivers structured, real-time data from the web using scalable APIs and no-code tools, removing the need to manage proxies, browsers, or anti-bot systems.
Visit Website
  • Google BigQuery Landing page
    Landing page //
    2023-10-03
  • HasData Landing page
    Landing page //
    2025-10-09
  • HasData HasData API's Playground
    HasData API's Playground //
    2025-10-09
  • HasData HasData No-Code Scrapers
    HasData No-Code Scrapers //
    2025-10-09

HasData is one of the best web scraping API platforms built for performance, stability, and scale. It delivers enterprise-grade APIs built for speed, reliability, and accuracy. Businesses that depend on live search data, competitive intelligence, and public web data trust HasData for its consistent performance and transparent infrastructure.

The HasData SERP API is one of the fastest and most reliable on the market. It processes millions of requests per hour with a median latency around 1.75 seconds, providing clean and complete Google Search results without dealing with captchas, proxy management, or rotating browser setups. HasDataโ€™s infrastructure scales horizontally across self-managed Kubernetes clusters to ensure zero downtime during heavy traffic bursts or sustained data-collection workloads.

The HasData Web Scraping API goes beyond search. It provides a unified, resilient system that handles complex scraping tasks automatically โ€” covering dynamic pages, anti-bot protection, and JavaScript rendering. Developers get structured JSON results instantly, with no need to handle HTML parsing, headless browsers, or maintenance overhead.

HasData offers a broad range of specialized APIs, covering key platforms including Google Maps, Zillow, Amazon, Indeed, and many more. Each API is designed for production-level use cases where uptime, precision, and response speed matter more than anything else. Whether for SEO monitoring, price intelligence, lead generation, or market analytics, HasData removes the technical pain points so teams can focus on data, not scraping infrastructure.

For companies that require the best scraping performance without operational risk, HasData is a proven choice. It combines real-time data extraction power, consistent reliability, and developer-friendly APIs to support everything from startups to large enterprises running millions of daily requests.

Google BigQuery

Website
cloud.google.com
Pricing URL
-
$ Details
Platforms
-
Edit details

HasData

Website
hasdata.com
Pricing URL
Official HasData Pricing
$ Details
Free Trial $49.0 / Monthly (Up to 200,000 Requests | 15 concurrent requests)
Platforms
Cloud Web Python Node JS PHP Go Zapier Browser
Startup details
Country
United States
State
TX
City
HOUSTON
Founder(s)
Roman Miliushkevich, Sergey Ermakovich
Employees
10 - 19
Edit details

Google BigQuery features and specs

  • Scalability
    BigQuery can effortlessly scale to handle large volumes of data due to its serverless architecture, thereby reducing the operational overhead of managing infrastructure.
  • Speed
    It leverages Google's infrastructure to provide high-speed data processing, making it possible to run complex queries on massive datasets in a matter of seconds.
  • Integrations
    BigQuery easily integrates with various Google Cloud Platform services, as well as other popular data tools like Looker, Tableau, and Power BI.
  • Automatic Optimization
    Features like automatic data partitioning and clustering help to optimize query performance without requiring manual tuning.
  • Security
    BigQuery provides robust security features including IAM roles, customer-managed encryption keys, and detailed audit logging.
  • Cost Efficiency
    The pricing model is based on the amount of data processed, which can be cost-effective for many use cases when compared to traditional data warehouses.
  • Managed Service
    Being fully managed, BigQuery takes care of database administration tasks such as scaling, backups, and patch management, allowing users to focus on their data and queries.

Possible disadvantages of Google BigQuery

  • Cost Predictability
    While the pay-per-use model can be cost-efficient, it can also make cost forecasting difficult. Unexpected large queries could lead to higher-than-anticipated costs.
  • Complexity
    The learning curve can be steep for those who are not already familiar with SQL or Google Cloud Platform, potentially requiring training and education.
  • Limited Updates
    BigQuery is optimized for read-heavy operations, and it can be less efficient for scenarios that require frequent updates or deletions of data.
  • Query Pricing
    Costs are based on the amount of data processed by each query, which may not be suitable for use cases that require frequent analysis of large datasets.
  • Data Transfer Costs
    While internal data movement within Google Cloud can be cost-effective, transferring data to or from other services or on-premises systems can incur additional costs.
  • Dependency on Google Cloud
    Organizations heavily invested in multi-cloud or hybrid-cloud strategies may find the dependency on Google Cloud limiting.
  • Cold Data Performance
    Query performance might be slower for so-called 'cold data,' or data that has not been queried recently, affecting the responsiveness for some workloads.

HasData features and specs

  • Sub-2s Median Latency
    Every API request completes in about 2.1 seconds on average, even under high load.
  • 99.9% uptime SLA
    Stay online with highly reliable servers, automated failover, and 24/7 infrastructure monitoring.
  • Up to 10M Requests/Hour
    Handle massive scraping operations with infrastructure built to support 10 million hourly API calls.
  • 100M+ Proxies
    Access hundreds of millions rotating IPs for global coverage and unblockable data collection.
  • JavaScript Rendering
    Extract content from dynamic, JavaScript-heavy websites without manual browser emulation.
  • Auto-Retry & Failover
    Built-in error handling and retries ensure high success rates even under volatile network conditions.
  • Clean Structured Output
    Deliver consistent, parsed JSON with metadata, images, text, listings, and links.
  • Full Anti-Bot Protection
    Bypasses Cloudflare, Datadome, and Akamai automatically โ€” no proxy rotation or browser setup required.
  • Easy Integration
    Connect in minutes using clear API documentation, SDKs, and straightforward REST architecture.

Analysis of Google BigQuery

Overall verdict

  • Google BigQuery is a powerful and flexible data warehouse solution that suits a wide range of data analytics needs. Its ability to handle large volumes of data quickly makes it a preferred choice for organizations looking to leverage their data effectively.

Why this product is good

  • Google BigQuery is a fully-managed data warehouse that simplifies the analysis of large datasets. It is known for its scalability, speed, and integration with other Google Cloud services. It supports standard SQL, has built-in machine learning capabilities, and allows for seamless data integration from various sources. The serverless architecture means that users don't need to worry about infrastructure management, and its pay-as-you-go model provides cost efficiency.

Recommended for

  • Businesses requiring fast processing of large datasets
  • Organizations that already utilize Google Cloud services
  • Companies looking for a cost-effective, scalable analytics solution
  • Teams interested in using SQL for data analysis
  • Data scientists integrating machine learning with their data workflows

Analysis of HasData

Overall verdict

  • HasData is a solid web scraping and data extraction platform that offers reliable APIs and tools for collecting structured data from websites, making it a good choice for businesses and developers needing scalable data solutions.

Why this product is good

  • Provides ready-to-use scraping APIs that handle proxies, CAPTCHAs, and JavaScript rendering automatically
  • Offers scalable infrastructure suitable for both small projects and large-scale data extraction needs
  • Supports structured data output formats like JSON and HTML for easy integration
  • Includes documentation and developer-friendly tools to speed up implementation
  • Handles anti-bot measures so users can focus on data rather than infrastructure

Recommended for

  • Developers building applications that require automated web data collection
  • Businesses conducting market research and competitor price monitoring
  • E-commerce companies tracking product data and reviews
  • Data analysts and researchers gathering large datasets from the web
  • SEO professionals monitoring search engine results and rankings

Google BigQuery videos

+ Add

Cloud Dataprep Tutorial - Getting Started 101

More videos:

  • Review - Advanced Data Cleanup Techniques using Cloud Dataprep (Cloud Next '19)
  • Demo - Google Cloud Dataprep Premium product demo

HasData videos

No HasData videos yet. You could help us improve this page by suggesting one.

Add video

Category Popularity

0-100% (relative to Google BigQuery and HasData)

Google BigQuery

HasData

Data Dashboard
100 100%
Data Dashboard
0% 0
Data Extraction
0 0%
Data Extraction
100% 100
Big Data
100 100%
Big Data
0% 0
Web Scraping
0 0%
Web Scraping
100% 100

Questions & Answers

As answered by people managing Google BigQuery and HasData.

What makes your product unique?

HasData's answer:

HasData combines high-speed infrastructure with intelligent web data extraction. Its APIs handle JavaScript rendering, IP rotation, and anti-bot bypassing at scaleโ€”without requiring additional tooling. Developers can integrate once and retrieve clean, reliable data instantly.

Why should a person choose your product over its competitors?

HasData's answer:

Choose HasData for performance, reliability, and simplicity. Its APIs deliver fast response times, high accuracy, and zero hidden limits. The platform is built for real-world scrapingโ€”resilient under load, stable in production, and trusted by high-volume users.

How would you describe the primary audience of your product?

HasData's answer:

HasData serves developers, data engineers, and businesses that need scalable, automated access to public web data. These users build tools, analytics platforms, and competitive intelligence systems powered by structured, real-time information.

What's the story behind your product?

HasData's answer:

HasData was created to eliminate the complexity of large-scale web scraping. Frustrated by fragile scripts, unreliable proxies, and blocked requests, the founders built a unified platform that turns scraping into a dependable API service.

Which are the primary technologies used for building your product?

HasData's answer:

HasData runs on a distributed infrastructure using Golang, Python, and Node.js. It leverages headless Chromium for rendering, Kubernetes for scaling, and global IP rotation systems for reliable data extraction across regions.

Who are some of the biggest customers of your product?

HasData's answer:

HasData serves leading companies in SEO, digital marketing, cybersecurity, and content intelligence. These clients rely on HasData to power large-scale data collection, competitive analysis, plagiarism detection, and local search insightsโ€”handling millions of requests per day without service disruption.

User comments

Share your experience with using Google BigQuery and HasData. For example, how are they different and which one is better?
Log in or Post with

Reviews

These are some of the external sources and on-site user reviews we've used to compare Google BigQuery and HasData

Google BigQuery Reviews

Database for Data Analytics
Processing typeDescriptionUse casesCommon databasesProcessing typesProcesses data in scheduled intervals (hours, days). High-latency but cost-efficient for large datasets.Financial reporting, trend analysis, historical analyticsSnowflake, Amazon Redshift, Google BigQueryContinuously ingests and processes data with minimal latency for real-time decision-making.Fraud...
Source: blog.devart.com
Data Warehouse Tools
Google BigQuery: Similar to Snowflake, BigQuery offers a pay-per-use model with separate charges for storage and queries. Storage costs start around $0.01 per GB per month, while on-demand queries are billed at $5 per TB processed.
Source: peliqan.io
Top 6 Cloud Data Warehouses in 2023
You can also use BigQueryโ€™s columnar and ANSI SQL databases to analyze petabytes of data at a fast speed. Its capabilities extend enough to accommodate spatial analysis using SQL and BigQuery GIS. Also, you can quickly create and run machine learning (ML) models on semi or large-scale structured data using simple SQL and BigQuery ML. Also, enjoy a real-time interactive...
Source: geekflare.com
Top 5 Cloud Data Warehouses in 2023
Google BigQuery is an incredible platform for enterprises that want to run complex analytical queries or โ€œheavyโ€ queries that operate using a large set of data. This means itโ€™s not ideal for running queries that are doing simple filtering or aggregation. So if your cloud data warehousing needs lightning-fast performance on a big set of data, Google BigQuery might be a great...
Source: www.shipyardapp.com
Top 5 BigQuery Alternatives: A Challenge of Complexity
BigQuery's emergence as an attractive analytics and data warehouse platform was a significant win, helping to drive a 45% increase in Google Cloud revenue in the last quarter. The company plans to maintain this momentum by focusing on a multi-cloud future where BigQuery advances the cause of democratized analytics.
Source: blog.panoply.io

HasData Reviews

We have no reviews of HasData yet.
Be the first one to post

Social recommendations and mentions

Based on our record, Google BigQuery seems to be more popular. It has been mentiond 47 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Google BigQuery mentions (47)

  • Ruby on Rails Performance: 7 Lessons from Scaling FirstPromoter
    We migrated the analytics layer to Google BigQuery. Same queries that timed out in PostgreSQL now run in under 2 seconds. But not everything belongs in BigQuery โ€” we initially moved too aggressively and actually reverted some queries back when the added complexity wasn't justified. Our rule of thumb: if a query scans hundreds of thousands of rows or involves complex time-series aggregations, BigQuery. Everything... - Source: dev.to / 4 months ago
  • How to Analyze 47 Million Hacker News Posts: A Data Scientist's Dream Dataset Just Got Better
    Google BigQuery - For large-scale data processing and SQL-based analysis. - Source: dev.to / 5 months ago
  • What if ML pipelines had a lock file?
    Data Pipelines usually read from tables that change over time. Most of these tables are stored in a data warehouse like Amazon Redshift or Google BigQuery. Rows are added or removed. Backfills happen. A column gets renamed or its meaning changes. Even when teams snapshot data, those snapshots are often implicit, not recorded as part of the pipeline run itself. - Source: dev.to / 6 months ago
  • Best SQL Courses with Certificates for 2026
    SQL endures because it's the non-negotiable interface for relational data. Enterprise data storage still relies heavily on relational databases despite new alternatives. What makes SQL valuable for learners is transferabilityโ€”while dialects differ across PostgreSQL, SQL Server, and BigQuery, the fundamentals stay consistent. - Source: dev.to / 8 months ago
  • Why Your Snowflake Bill is High and How to Fix It with a Hybrid Approach
    Within classic cloud data warehouses, Google BigQuery presents a different pricing model. Its on-demand, per-terabyte-scanned pricing can be cost-effective for sporadic forensic queries. But it carries the risk of a runaway query where a single mistake leads to a massive bill. - Source: dev.to / 9 months ago
View more

HasData mentions (0)

We have not tracked any mentions of HasData yet. Tracking of HasData recommendations started around Oct 2025.

What are some alternatives?

When comparing Google BigQuery and HasData, you can also consider the following products

Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.โ€ŽWhat is Apache Spark?

Apify - Apify is a web scraping and automation platform that can turn any website into an API.

Looker - Looker makes it easy for analysts to create and curate custom data experiencesโ€”so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.

ScrapingBee - ScrapingBee is a Web Scraping API that handles proxies and Headless browser for you, so you can focus on extracting the data you want, and nothing else.

Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.

Zyte - We're Zyte (formerly Scrapinghub), the central point of entry for all your web data needs.

Loading...