Airbyte
Open-source data integration engine for ELT pipelines across data sources
Open-Source Projects
Discover top open-source software, updated regularly with real-world adoption signals.
Discover top open-source software, updated regularly with real-world adoption signals.
Declarative code-first data integration engine for modern pipelines
Meltano is a Python-based data integration engine that connects 600+ APIs and databases through declarative configuration, eliminating custom integration code.
Meltano is a declarative, code-first data integration engine built for data engineers and teams who need reliable, scalable pipelines without the overhead of custom API integrations. Built on Python and leveraging the Singer ecosystem, it provides access to 600+ pre-built connectors for APIs and databases through simple YAML configuration.
Designed with version control and CI/CD workflows in mind, Meltano treats data pipelines as code. Teams can define, test, and deploy ELT workflows using declarative configuration files, making pipelines reproducible and maintainable. The platform integrates seamlessly with modern data stacks and supports containerized deployments through optimized Docker images.
Meltano Hub serves as the central registry for discovering and sharing plugins, taps, and targets. With an active community of 2,500+ data professionals and MIT licensing, the project benefits from continuous contributions and a growing connector ecosystem. Whether you're building ML pipelines or consolidating data from multiple sources, Meltano provides the foundation for scalable data operations.
When teams consider Meltano, these hosted platforms usually appear on the same shortlist.
Looking for a hosted option? These are the services engineering teams benchmark against before choosing open source.
Multi-Source Data Consolidation
Centralize data from 600+ APIs and databases into a data warehouse using declarative configuration without custom integration code.
ML Pipeline Data Preparation
Build reproducible ELT workflows that extract, transform, and load training data from multiple sources for machine learning models.
GitOps-Driven Analytics Infrastructure
Version control data pipelines as code, enabling peer review, automated testing, and CI/CD deployment of data workflows.
Cloud-Native Data Operations
Deploy containerized data pipelines with optimized Docker images supporting cloud storage and multiple database connectors.
Meltano uses a declarative, code-first approach where pipelines are defined in version-controlled YAML files rather than GUI-based configurations, enabling GitOps workflows and CI/CD integration.
Meltano provides access to 600+ APIs and databases through its Hub, which aggregates Singer taps, targets, and community-contributed plugins.
While Meltano is built in Python, basic usage requires only YAML configuration. Python knowledge is helpful for custom plugin development or advanced transformations.
Meltano offers slim images (recommended, with cloud storage support) and full images (including all database connectors and build tools) on Docker Hub.
Yes, users can create and contribute plugins to Meltano Hub, making them immediately discoverable and usable by the community.
Project at a glance
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