Best Data Integration Tools for Docker
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Compare the Top Data Integration Tools that integrate with Docker as of July 2025
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This a list of Data Integration tools 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 Data Integration Tools for Docker?
Data integration tools help organizations combine data from multiple sources into a unified, coherent system for analysis and decision-making. These tools streamline the process of gathering, transforming, and loading data (ETL) from various databases, applications, and cloud services, ensuring consistent data across platforms. They provide features like data cleansing, mapping, and real-time synchronization, ensuring data accuracy and reliability. With automated workflows and connectors, data integration tools reduce manual effort and eliminate data silos, improving operational efficiency. Ultimately, they enable businesses to make better, data-driven decisions by providing a comprehensive view of their information landscape. Compare and read user reviews of the best Data Integration tools for Docker currently available using the table below. This list is updated regularly.
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1
Stackable
Stackable
The Stackable data platform was designed with openness and flexibility in mind. It provides you with a curated selection of the best open source data apps like Apache Kafka, Apache Druid, Trino, and Apache Spark. While other current offerings either push their proprietary solutions or deepen vendor lock-in, Stackable takes a different approach. All data apps work together seamlessly and can be added or removed in no time. Based on Kubernetes, it runs everywhere, on-prem or in the cloud. stackablectl and a Kubernetes cluster are all you need to run your first stackable data platform. Within minutes, you will be ready to start working with your data. Configure your one-line startup command right here. Similar to kubectl, stackablectl is designed to easily interface with the Stackable Data Platform. Use the command line utility to deploy and manage stackable data apps on Kubernetes. With stackablectl, you can create, delete, and update components.Starting Price: Free -
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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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Meltano
Meltano
Meltano provides the ultimate flexibility in deployment options. Own your data stack, end to end. Ever growing connector library of 300+ connectors have been running in production for years. Run workflows in isolated environments, execute end-to-end tests, and version control everything. Open source gives you the power to build your ideal data stack. Define your entire project as code and collaborate confidently with your team. The Meltano CLI enables you to rapidly create your project, making it easy to start replicating data. Meltano is designed to be the best way to run dbt to manage your transformations. Your entire data stack is defined in your project, making it simple to deploy it to production. Validate your changes in development before moving to CI, and in staging before moving to production.
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