Best ETL Software for Docker

IRI Voracity is an end-to-end software platform for fast, affordable, and ergonomic data lifecycle management. Voracity speeds, consolidates, and often combines the key activities of data discovery, integration, migration, governance, and analytics in a single pane of glass, built on Eclipse™. Through its revolutionary convergence of capability and its wide range of job design and runtime options, Voracity bends the multi-tool cost, difficulty, and risk curves away from megavendor ETL packages, disjointed Apache projects, and specialized software. Voracity uniquely delivers the ability to perform data: * profiling and classification * searching and risk-scoring * integration and federation * migration and replication * cleansing and enrichment * validation and unification * masking and encryption * reporting and wrangling * subsetting and testing Voracity runs on-premise, or in the cloud, on physical or virtual machines, and its runtimes can also be containerized or called from real-time applications or batch jobs.

Meltano offers unparalleled flexibility in how you can deploy your data solutions. Take complete ownership of your data infrastructure from start to finish. With an extensive library of over 300 connectors that have been successfully operating in production for several years, you have a wealth of options at your fingertips. You can execute workflows in separate environments, perform comprehensive end-to-end tests, and maintain version control over all your components. The open-source nature of Meltano empowers you to create the ideal data setup tailored to your needs. By defining your entire project as code, you can work collaboratively with your team with confidence. The Meltano CLI streamlines the project creation process, enabling quick setup for data replication. Specifically optimized for managing transformations, Meltano is the ideal platform for running dbt. Your entire data stack is encapsulated within your project, simplifying the production deployment process. Furthermore, you can validate any changes made in the development phase before progressing to continuous integration, and subsequently to staging, prior to final deployment in production. This structured approach ensures a smooth transition through each stage of your data pipeline.