Software Alternatives, Accelerators & Startups

Pandas VS HasData

Compare Pandas VS HasData and see what are their differences

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Pandas logo Pandas

Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

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.
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  • Pandas Landing page
    Landing page //
    2023-05-12
  • 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.

HasData

$ Details
Free Trial $49 / 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

Pandas features and specs

  • Data Wrangling
    Pandas offers robust tools for manipulating, cleaning, and transforming data, making it easier to prepare data for analysis.
  • Flexible Data Structures
    Pandas provides two primary data structures: Series and DataFrame, which are flexible and offer powerful capabilities for handling various types of datasets.
  • Integration with Other Libraries
    Pandas integrates seamlessly with other Python libraries such as NumPy, Matplotlib, and SciPy, facilitating comprehensive data analysis workflows.
  • Performance with Data Size
    For data sizes that fit into memory, Pandas performs excellently with operations and computations being highly optimized.
  • Rich Feature Set
    Pandas provides a wide array of functionalities, including but not limited to group-by operations, merging and joining data sets, time-series functionality, and input/output tools.
  • Community and Documentation
    Pandas has a strong community and extensive documentation, offering a wealth of tutorials, examples, and support for new and experienced users alike.

Possible disadvantages of Pandas

  • Memory Consumption
    Pandas can become memory inefficient with very large datasets because it relies heavily on in-memory operations.
  • Single-threaded
    Many Pandas operations are single-threaded, which can lead to performance bottlenecks when handling very large datasets.
  • Steep Learning Curve
    For users who are new to data analysis or Pandas, there can be a steep learning curve due to its extensive capabilities and complex syntax at times.
  • Less Suitable for Real-time Analytics
    Pandas is not designed for real-time analytics and is better suited for batch processing due to its in-memory operations and single-threaded nature.
  • Error Handling
    Error messages in Pandas can sometimes be cryptic and hard to interpret, making debugging a challenge for users.

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 Pandas

Overall verdict

  • Pandas is highly recommended for tasks involving data manipulation and analysis, especially for those working with tabular data. Its efficiency and ease of use make it a staple in the data science toolkit.

Why this product is good

  • Pandas is widely considered a good library for data manipulation and analysis due to its powerful data structures, like DataFrames and Series, which make it easy to work with structured data. It provides a wide array of functions for data cleaning, transformation, and aggregation, which are essential tasks in data analysis. Furthermore, Pandas seamlessly integrates with other libraries in the Python ecosystem, making it a versatile tool for data scientists and analysts. Its extensive documentation and strong community support also contribute to its reputation as a reliable tool for data analysis tasks.

Recommended for

    Pandas is particularly recommended for data scientists, analysts, and engineers who need to perform data cleaning, transformation, and analysis as part of their work. It is also suitable for academics and researchers dealing with data in various formats and needing powerful tools for their data-driven research.

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

Pandas videos

Ozzy Man Reviews: Pandas

More videos:

  • Review - Ozzy Man Reviews: PANDAS Part 2
  • Review - Trash Pandas Review with Sam Healey

HasData videos

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

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Category Popularity

0-100% (relative to Pandas and HasData)
Data Science And Machine Learning
Data Extraction
0 0%
100% 100
Data Science Tools
100 100%
0% 0
Web Scraping
0 0%
100% 100

Questions & Answers

As answered by people managing Pandas 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

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Reviews

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

Pandas Reviews

25 Python Frameworks to Master
Pandas is a powerful and flexible open-source library used to perform data analysis in Python. It provides high-performance data structures (i.e., the famous DataFrame) and data analysis tools that make it easy to work with structured data.
Source: kinsta.com
Python & ETL 2020: A List and Comparison of the Top Python ETL Tools
When it comes to ETL, you can do almost anything with Pandas if you're willing to put in the time. Plus, pandas is extraordinarily easy to run. You can set up a simple script to load data from a Postgre table, transform and clean that data, and then write that data to another Postgre table.
Source: www.xplenty.com

HasData Reviews

We have no reviews of HasData yet.
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Social recommendations and mentions

Based on our record, Pandas seems to be more popular. It has been mentiond 231 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.

Pandas mentions (231)

  • MLOps Lifecycle: Stages, Workflow, and Best Practices
    Feature transformations should be deterministic: The same input should produce the same output when the same feature definition and configuration are applied. This is what allows training, backtesting, and live inference to remain aligned. Tools such as Pandas, Spark, or feature platforms such as Feast can be used to implement that logic. - Source: dev.to / 3 months ago
  • What Training Exists for Security Professionals Learning AI and Data Science?
    For early-career security practitioners (0-3 years). Start with Python literacy if you do not have it. The free Python Crash Course book and the pandas getting-started guide are enough to bootstrap. Then a hands-on applied course: GTK Cyber's Applied Data Science & AI for Cybersecurity and SANS SEC595 are both reasonable starting points. The goal at this stage is to be able to load a Zeek conn.log into a pandas... - Source: dev.to / 3 months ago
  • Best AI Cybersecurity Training for Security Teams: How to Evaluate the Options
    Python and data engineering for security data. Pandas for ingesting Zeek, Sysmon, EDR, and SIEM exports. Timestamp normalization to UTC, join keys across heterogeneous sources, feature extraction from raw logs. Without this layer, the ML content downstream is theater. - Source: dev.to / 3 months ago
  • Best AI Cybersecurity Training for Security Teams: How to Pick
    Pre-configured environment. A working VM or container with Jupyter, pandas, scikit-learn, and transformers already installed. Realistic security datasets loaded. GTK Cyber students work in the Centaur VM, a free Apache 2.0 portable lab. If the first hour of training is fighting CUDA installs, the course is not ready. - Source: dev.to / 3 months ago
  • Introduction to Python for Data Analysis: A Beginnerโ€™s Guide
    Pandas url is the most widely used library for data manipulation. - Source: dev.to / 3 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 Pandas and HasData, you can also consider the following products

NumPy - NumPy is the fundamental package for scientific computing with Python

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

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

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.

OpenCV - OpenCV is the world's biggest computer vision library

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