Best Big Data Platforms for Python
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Compare the Top Big Data Platforms that integrate with Python as of June 2025
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This a list of Big Data platforms that integrate with Python. Use the filters on the left to add additional filters for products that have integrations with Python. View the products that work with Python in the table below.
What are Big Data Platforms for Python?
Big data platforms are systems that provide the infrastructure and tools needed to store, manage, process, and analyze large volumes of structured and unstructured data. These platforms typically offer scalable storage solutions, high-performance computing capabilities, and advanced analytics tools to help organizations extract insights from massive datasets. Big data platforms often support technologies such as distributed computing, machine learning, and real-time data processing, allowing businesses to leverage their data for decision-making, predictive analytics, and process optimization. By using these platforms, organizations can handle complex datasets efficiently, uncover hidden patterns, and drive data-driven innovation. Compare and read user reviews of the best Big Data platforms for Python currently available using the table below. This list is updated regularly.
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1
Gigasheet
Gigasheet
Gigasheet is the big data spreadsheet that requires no set up, training, database or coding skills. If you can use a spreadsheet, you can find opportunities in big data. Best of all, your first 3GB are free! Use Gigasheet to filter, sort, group and aggregate data to gain insights. Create pivot tables by simply dragging columns around. Data cleanup tools and functions clean and insert data during analysis. Enrichments such as Email Validation and Geo IP Location look up make your data even more useful. Sharing and collaboration tools make distributing huge data sets a snap. Gigasheet integrates with more than 135 SaaS platforms and databases. Thousands of individuals and teams use Gigasheet to gain insights in minutes, not hours or days. You don't need to be a data scientist to get answers from big data.Starting Price: $95 per month -
2
DataWorks
Alibaba Cloud
DataWorks is a Big Data platform product launched by Alibaba Cloud. It provides one-stop Big Data development, data permission management, offline job scheduling, and other features. DataWorks works straight ‘out-the-box’ without the need to worry about complex underlying cluster establishment and operations & management. You can drag and drop nodes to create a workflow. You can also edit and debug your code online, and ask other developers to join you. Supports data integration, MaxCompute SQL, MaxCompute MR, machine learning, and shell tasks. Supports task monitoring and sends alarms when errors occur to avoid service interruptions. Runs millions of tasks concurrently and supports hourly, daily, weekly, and monthly schedules. DataWorks is the best platform for building big data warehouses and provides comprehensive data warehousing services. DataWorks provides a full solution for data aggregation, data processing, data governance, and data services. -
3
kdb Insights
KX
kdb Insights is a cloud-native, high-performance analytics platform designed for real-time analysis of both streaming and historical data. It enables intelligent decision-making regardless of data volume or velocity, offering unmatched price and performance, and delivering analytics up to 100 times faster at 10% of the cost compared to other solutions. The platform supports interactive data visualization through real-time dashboards, facilitating instantaneous insights and decision-making. It also integrates machine learning models to predict, cluster, detect patterns, and score structured data, enhancing AI capabilities on time-series datasets. With supreme scalability, kdb Insights handles extensive real-time and historical data, proven at volumes of up to 110 terabytes per day. Its quick setup and simple data intake accelerate time-to-value, while native support for q, SQL, and Python, along with compatibility with other languages via RESTful APIs. -
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Databricks Data Intelligence Platform
Databricks
The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. The winners in every industry will be data and AI companies. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals. Databricks combines generative AI with the unification benefits of a lakehouse to power a Data Intelligence Engine that understands the unique semantics of your data. This allows the Databricks Platform to automatically optimize performance and manage infrastructure in ways unique to your business. The Data Intelligence Engine understands your organization’s language, so search and discovery of new data is as easy as asking a question like you would to a coworker. -
5
Vaex
Vaex
At Vaex.io we aim to democratize big data and make it available to anyone, on any machine, at any scale. Cut development time by 80%, your prototype is your solution. Create automatic pipelines for any model. Empower your data scientists. Turn any laptop into a big data powerhouse, no clusters, no engineers. We provide reliable and fast data driven solutions. With our state-of-the-art technology we build and deploy machine learning models faster than anyone on the market. Turn your data scientist into big data engineers. We provide comprehensive training of your employees, enabling you to take full advantage of our technology. Combines memory mapping, a sophisticated expression system, and fast out-of-core algorithms. Efficiently visualize and explore big datasets, and build machine learning models on a single machine. -
6
Polars
Polars
Knowing of data wrangling habits, Polars exposes a complete Python API, including the full set of features to manipulate DataFrames using an expression language that will empower you to create readable and performant code. Polars is written in Rust, uncompromising in its choices to provide a feature-complete DataFrame API to the Rust ecosystem. Use it as a DataFrame library or as a query engine backend for your data models. -
7
Row Zero
Row Zero
Row Zero is the best spreadsheet for big data. Row Zero matches the experience of traditional spreadsheets but can handle 1+ billion rows, process data much faster, and connect live to your data warehouse and other data sources. Row Zero spreadsheets are powerful enough to pull entire database tables into a spreadsheet, letting non-technical users build live pivot tables, graphs, models, and metrics on data from your data warehouse. Row Zero also offers advanced security features and is cloud-based, empowering organizations to eliminate ungoverned CSV exports and locally stored spreadsheets from their org. With Row Zero, you can easily open, edit, and share multi-GB files (CSV, parquet, txt, etc.) Row Zero has all of the spreadsheet features you know and love, but was built for big data. If you know how to use Excel or Google Sheets, you can get started with ease.Starting Price: $8/month/user
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