head to head · open source
debezium vs metorikku
debezium has 13,130 GitHub stars, 3,042 forks, 131 open issues and last shipped today. metorikku has 589 stars, 156 forks, 65 open issues and last shipped 17 days ago. debezium leads on adoption by 2,129% (13,130 vs 589 stars). debezium is written in Java under Apache-2.0; metorikku is written in Scala under MIT. debezium has attracted 23% as many forks as stars, metorikku 26%. debezium was the more recently maintained of the two, and both are self-hostable with no licence fee.
Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.
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Side by side
| debezium | metorikku | |
|---|---|---|
| GitHub stars | ★ 13K | ★ 589 |
| License | Apache-2.0 | MIT |
| Written in | Java | Scala |
| Last push | 2026-09-18 | 2026-09-01 |
| Forks | ⑂ 3.0K | ⑂ 156 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick debezium if
- You weight community size — 13K stars and counting
- You want the Apache-2.0 license terms
- Your stack matches Java
- You value the larger contributor base for long-term maintenance
pick metorikku if
- You want the metorikku feature set and don't need the biggest community
- You prefer the MIT license terms
- Your stack matches Scala
- You evaluated both and metorikku fits your workflow better
About debezium
Debezium is an open source, low latency change data capture (CDC) platform that monitors databases and turns every row level change into an ordered event stream that applications consume, and it is built for Java teams already running Apache Kafka and Kafka Connect.
read the full debezium overview →
About metorikku
Metorikku is a library that simplifies writing and executing ETLs on top of Apache Spark. It is based on simple YAML configuration files and runs on any Spark cluster. The platform also includes a simple way to write unit and E2E tests. Getting started To run Metorikku you must first define 2 files. Metric file A metric file defines the steps and queries of the ETL as well as where and what to output. For example a simple configuration YAML (JSON is also supported) should be as follows: yaml metric: "/path/to/metric" mocks: name: table 1 path: mocks/table 1.jsonl tests: df2: id: 200 name: test id: 300 name: test2…
read the full metorikku overview →
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Frequently asked questions
Is debezium or metorikku more popular?
debezium has 13,130 GitHub stars and metorikku has 589. debezium has the larger community by that measure.
Are debezium and metorikku free?
Both are open source. debezium is licensed under Apache-2.0 and metorikku under MIT. Neither carries a licence fee.
What is the difference between debezium and metorikku?
debezium is written in Java and metorikku in Scala. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.
Which should I choose, debezium or metorikku?
Choose debezium if you want the larger community (13,130 stars) or its Apache-2.0 licence terms. Choose metorikku if its feature set, stack or MIT licence fits better. Both are self-hostable.