Best Big Data Platforms for Docker

Compare the Top Big Data Platforms that integrate with Docker as of October 2025

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This a list of Big Data platforms that integrate with Docker. Use the filters on the left to add additional filters for products that have integrations with Docker. View the products that work with Docker in the table below.

What are Big Data Platforms for Docker?

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 Docker currently available using the table below. This list is updated regularly.

1

Deepnote

Deepnote

Deepnote is building the best data science notebook for teams. In the notebook, users can connect their data, explore, and analyze it with real-time collaboration and version control. Users can easily share project links with team collaborators, or with end-users to present polished assets. All of this is done through a powerful, browser-based UI that runs in the cloud. We built Deepnote because data scientists don't work alone. Features: - Sharing notebooks and projects via URL - Inviting others to view, comment and collaborate, with version control - Publishing notebooks with visualizations for presentations - Sharing datasets between projects - Set team permissions to decide who can edit vs view code - Full linux terminal access - Code completion - Automatic python package management - Importing from github - PostgreSQL DB connection

Starting Price: Free

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2

IRI Voracity

IRI, The CoSort Company

Voracity is the only high-performance, all-in-one data management platform accelerating AND consolidating the key activities of data discovery, integration, migration, governance, and analytics. Voracity helps you control your data in every stage of the lifecycle, and extract maximum value from it. Only in Voracity can you: 1) CLASSIFY, profile and diagram enterprise data sources 2) Speed or LEAVE legacy sort and ETL tools 3) MIGRATE data to modernize and WRANGLE data to analyze 4) FIND PII everywhere and consistently MASK it for referential integrity 5) Score re-ID risk and ANONYMIZE quasi-identifiers 6) Create and manage DB subsets or intelligently synthesize TEST data 7) Package, protect and provision BIG data 8) Validate, scrub, enrich and unify data to improve its QUALITY 9) Manage metadata and MASTER data. Use Voracity to comply with data privacy laws, de-muck and govern the data lake, improve the reliability of your analytics, and create safe, smart test data

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3

jethro

jethro

Data-driven decision-making has unleashed a surge of business data and a rise in user demand to analyze it. This trend drives IT departments to migrate off expensive Enterprise Data Warehouses (EDW) toward cost-effective Big Data platforms like Hadoop or AWS. These new platforms come with a Total Cost of Ownership (TCO) that is about 10 times lower. They are not ideal for interactive BI applications, however, as they fail to match the high performance and user concurrency of legacy EDWs. For this exact reason, we developed Jethro. Customers use Jethro for interactive BI on Big Data. Jethro is a transparent middle tier that requires no changes to existing apps or data. It is self-driving with no maintenance required. Jethro is compatible with BI tools like Tableau, Qlik, and Microstrategy and is data source agnostic. Jethro delivers on the demands of business users allowing for thousands of concurrent users to run complicated queries over billions of records.

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4

Astro by Astronomer

Astronomer

For data teams looking to increase the availability of trusted data, Astronomer provides Astro, a modern data orchestration platform, powered by Apache Airflow, that enables the entire data team to build, run, and observe data pipelines-as-code. Astronomer is the commercial developer of Airflow, the de facto standard for expressing data flows as code, used by hundreds of thousands of teams across the world.

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5

Wavo

Wavo

We’ve released a revolutionary big data platform that gathers all information about a music business, providing a single source of truth for decisions. Every music business has hundreds of data sources. But they are siloed and fragmented. Our platform identifies and connects them to build a foundation of quality data that can be applied to all daily music business operations. To work efficiently and securely—and to surface valuable insight no one else can—record labels and agencies require a sophisticated data management and governance system, so that data is available, relevant, and usable at all times. As data sources are ingested into Wavo’s Big Data Platform, machine learning is deployed to tag data based on personalized templates, making it easy to access and drill-down into important information. This enables everyone in a music business to activate and deliver business-ready data, backed up and organized for immediate value.

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