Meltano

Meltano is an open-source ELT and data integration platform for engineering-led data teams, run self-hosted or as a managed cloud priced by compute hours.

Meltano moves data out of SaaS applications, databases and files and into a warehouse, with every pipeline kept as code in a Git repository. The data integration platform handles the extract, load and transform steps of an ELT job in one run. Meltano Limited builds it in London, and in 2026 Matatika and Meltano came together under the Meltano name as one company. The engine reads from sources through connectors listed in Meltano Hub, and engineers write new ones with the Meltano SDK when a source is missing. The meltano select command picks the tables and columns to load, and stream maps hash, filter or rename a column while the data is in flight. Replication runs key-based incremental or log-based from a database's transaction log, depending on the connector. After the load, dbt models run in the warehouse within the same meltano run command. Meltano Cloud adds managed workspaces, cron schedules, failure alert emails with Pipeline Diagnosis, and Agent Melty, an AI data engineer agent that drafts pipeline configuration from a plain request. The product suits engineering-led data teams who review pipeline changes the way they review application code. Analytics engineers already working in dbt get extraction and loading in the same project. Agencies keep each client in its own workspace, and larger organisations split pipelines by business unit or by environment. Meltano Open, the self-hosted edition, fits teams with a DevOps crew who will run the infrastructure, monitoring and uptime themselves. Meltano Cloud fits teams who would rather have Meltano run that side, with Meltano engineers reachable over Slack. A typical job pulls CRM and product data into Snowflake, BigQuery or PostgreSQL every few minutes on a cron schedule. Personal data columns are hashed by a stream map before they land, and dbt then builds the reporting models. Changes move from a dev workspace to staging and on to production, with the history of each change kept in Git. Teams that orchestrate with Apache Airflow call Meltano jobs from their DAGs, and Cloud logs can stream to Datadog. Reverse ETL then sends the modelled results back into the business tools where sales and support teams work.