olake
OLake is an open-source data ingestion engine that replicates data from databases (Postgres, MySQL, MongoDB, Oracle, MSSQL, DB2), Kafka, and S3 into Apache Iceberg tables or Parquet files. It handles both full-load and change-data-capture (CDC) scenarios with claimed high throughput (580K RPS for Postgres) and includes a self-serve UI for configuration.
Key facts
Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.
| Field | Value |
|---|---|
| Repository | datazip-inc/olake |
| Owner | datazip-inc |
| Primary language | Go |
| License | Apache-2.0 — OSI-approved |
| Stars | 1.4k |
| Forks | 236 |
| Open issues | 145 |
| Latest release | v0.8.0 (2026-07-03) |
| Last updated | 2026-07-08 |
| Source | https://github.com/datazip-inc/olake |
What olake is
Written in Go, OLake provides CDC connectors using native mechanisms (pgoutput for Postgres, binlog for MySQL, oplog for MongoDB), writes to Iceberg with support for Glue, Hive, JDBC, and REST catalogs (Nessie, Polaris, Unity, Lakekeeper, AWS S3 Tables), and optionally to Parquet. Supports schema discovery and evolution without requiring Spark, Flink, or Debezium.
Get the olake source
Clone the repository and explore it locally.
git clone https://github.com/datazip-inc/olake.gitcd olake# follow the project's README for install & configurationNeed it deployed, integrated, or customized instead? DEV.co ships production installs.
Best use cases
Implementation considerations
- Benchmarks cited (580K RPS Postgres, 338K RPS MySQL) are proprietary claims published on olake.io/docs; independent verification recommended for throughput-critical projects.
- Latest release v0.8.0 (2026-07-03) and 145 open issues suggest active development; stability varies by connector (Postgres/MySQL mature, Oracle CDC in progress).
- Schema evolution is automatic but requires validation; monitor catalog consistency and test failover/rollback procedures before production.
- Deployment via Docker Compose is straightforward; however, scaling CDC at high throughput may require tuning connection pools, memory, and checkpoint mechanisms.
- State management (offsets, checkpoints) depends on the destination catalog; use JDBC or REST catalogs with durable metastores for production.
When to avoid it — and what to weigh
- Heavy ETL Transformations Required — OLake focuses on replication and ingestion, not transformation. Complex data cleaning, aggregation, or business logic requires downstream tooling.
- Sub-Second Latency Criticality — Designed for near-real-time analytics, not event-streaming or sub-second transaction mirroring. Kafka CDC is bounded incremental only, not continuous.
- Small/Experimental Projects with Minimal Ops Budget — Requires operational ownership (monitoring, scaling, configuration management). Managed SaaS alternatives may reduce operational burden for teams avoiding infrastructure.
- Oracle CDC at Scale (Work-in-Progress) — Oracle CDC is marked as WIP. Production deployments should verify status and rely on full-load + incremental queries until CDC is stable.
License & commercial use
Licensed under Apache License 2.0 (Apache-2.0), a permissive OSI-approved license permitting commercial use, modification, and distribution with minimal restrictions.
Apache-2.0 permits commercial use, but this is an actively maintained open-source project by Datazip Inc with no explicit commercial support SLA stated in the README. Consider reviewing whether the company offers support contracts or enterprise features separately.
DEV.co evaluation signals
Editorial assessment — not user reviews. Directional, with an explicit confidence level.
| Signal | Assessment |
|---|---|
| Maintenance | Active |
| Documentation | Adequate |
| License clarity | Clear |
| Deployment complexity | Moderate |
| DEV.co fit | Good |
| Assessment confidence | Medium |
No explicit security posture or vulnerability disclosure statement provided in README. Standard practices apply: validate SSL/TLS for database and S3 connections, manage credentials via environment variables or secrets manager, audit IAM policies for cloud storage, restrict network access to OLake services. Conduct security review before production deployment.
Alternatives to consider
Fivetran
Managed SaaS alternative with broader connector library and turnkey support; OLake claims 1.5–12.5× faster throughput but requires operational ownership.
Airbyte
Open-source and managed hybrid; simpler extensibility and larger community, but uses different underlying architecture (Python-based, less optimized for CDC throughput).
Debezium + Kafka + Flink
Modular CDC stack with strong Kafka integration; OLake trades flexibility for simplicity and no external dependencies, but Debezium offers richer connectors and mature operations tooling.
Build on olake with DEV.co software developers
Review the detailed implementation guide, verify connector maturity for your sources, and test throughput benchmarks in your environment. Contact the community on Slack for production support questions.
Talk to DEV.coRelated on DEV.co
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olake FAQ
How does OLake compare to Debezium in CDC capability?
Can I use OLake without Apache Iceberg?
Is Oracle CDC production-ready?
What operational overhead should I expect?
Work with a software development agency
From first prototype to production, DEV.co delivers software development services around tools like olake. Our software development agency staffs experienced software developers and web developers for custom software development, web development, integrations, and ongoing support across open-source databases and beyond.
Ready to evaluate OLake for your data pipeline?
Review the detailed implementation guide, verify connector maturity for your sources, and test throughput benchmarks in your environment. Contact the community on Slack for production support questions.