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olake

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Published: Oct 21, 2026 License: Apache-2.0 Imports: 7 Imported by: 10

README ΒΆ

olake
OLake Go

OLake Go is a high-performance, open-source data ingestion engine for replicating databases, S3, and Kafka into Apache Iceberg (or plain Parquet).
Built for scalable, real-time pipelines, OLake Go provides a simple web UI and CLI - used to ingest into vendor-lock-in free Iceberg tables supporting all the query-engines/warehouses.

Read the docs and benchmarks at olake.io/docs. Join our active community on Slack.

GitHub issues Documentation slack Contribute to OLake

[!NOTE] πŸŽ‰ OLake Fusion is now live! β€” Automate your Apache Iceberg Table Maintenance. Check it out here β†’ github.com/datazip-inc/olake-fusion πŸŽ‰

OLake Go β€” Super-fast Sync to Apache Iceberg

OLake Go supports replication from transactional databases such as PostgreSQL, MySQL, MongoDB, Oracle, DB2, and MSSQL, event-streaming systems like Apache Kafka and Object-store like S3, into open data lakehouse formats such as Apache Iceberg or Plain Parquet β€” delivering blazing-fast performance with minimal infrastructure cost.

pic


πŸš€ Why OLake Go?

  • 🧠 Smart sync: Full + CDC replication with automatic schema discovery & schema evolution
  • ⚑ High throughput: 580K RPS (Postgres) & 139K RPS (MySQL)
  • ➑️ Exactly once delivery & Arrow writes: Accuracy with speed.
  • πŸ’Ύ Iceberg-native: Supports Glue, Hive, JDBC, REST catalogs
  • πŸ–₯️ Self-serve UI: Deploy via Docker Compose and sync in minutes
  • πŸ’Έ Infra-light: No Spark, no Flink, no Kafka, no Debezium

πŸ“Š Benchmarks

Full Load
Source β†’ Destination Full Load Relative Performance (Full Load) Full Report
Postgres β†’ Iceberg
(as of 30th Jan 2026)
5,80,113 RPS 12.5Γ— faster than Fivetran Full Report
MySQL β†’ Iceberg
(as of 30th May 2026)
1,39,773 RPS 1.91Γ— faster than Fivetran Full Report
MongoDB β†’ Iceberg
(as of 5th Feb 2026)
37,879 RPS - Full Report
Oracle β†’ Iceberg
(as of 30th Jan 2026)
5,26,337 RPS - Full Report
Kafka β†’ Iceberg
(as of 27th Feb 2026)
2,09,065 MPS (Bounded Incremental) 1.23x slower than Flink Full Report
MSSQL β†’ Iceberg
(as of 09th June 2026)
3,45,866 RPS 4.32x faster than Fivetran Full Report
CDC
Source β†’ Destination CDC Relative Performance (CDC) Full Report
Postgres β†’ Iceberg
(as of 30th Jan 2026)
55,555 RPS 2Γ— faster than Fivetran Full Report
MySQL β†’ Iceberg
(as of 30th May 2026)
59,951 RPS 1.52Γ— faster than Fivetran Full Report
MongoDB β†’ Iceberg
(as of 5th Feb 2026)
10,692 RPS - Full Report

πŸ”§ Supported Sources and Destinations

Sources (Databases)
Source Full Load CDC Incremental Notes Documentation
PostgreSQL βœ… βœ… pgoutput βœ… wal2json deprecated Postgres Docs
MySQL βœ… βœ… βœ… Binlog-based CDC MySQL Docs
MongoDB βœ… βœ… βœ… Oplog-based CDC MongoDB Docs
Oracle βœ… WIP βœ… JDBC based Full Load & Incremental Oracle Docs
DB2 βœ… - βœ… JDBC based Full Load & Incremental DB2 Docs
MSSQL βœ… βœ… βœ… Full Load, CDC & Incremental MSSQL Docs
Source (S3)
Source Full Load CDC Incremental Notes Documentation
S3 βœ… - βœ… Ingests from Amazon S3 or S3-compatible (MinIO, LocalStack) S3 Docs
Source (Kafka)
Source Bounded Incremental Notes Documentation
Kafka βœ… Latest offset bounded incremental sync Kafka Docs
Destinations
Destination Format Supported Catalogs
Iceberg βœ… Glue, Hive, JDBC, REST (Nessie, Polaris, Unity, Lakekeeper, AWS S3 tables)
Parquet βœ… Filesystem
Writer Docs
  1. Apache Iceberg Docs

    1. Catalogs
      1. AWS Glue Catalog
      2. REST Catalog
        • Generic
        • Lakekeeper
        • Nessie
        • S3 Tables
        • Unity
        • Apache Polaris
      3. JDBC Catalog
      4. Hive Catalog
    2. Azure ADLS Gen2
    3. Google Cloud Storage (GCS)
    4. MinIO (local)
  2. Parquet Writer

    1. AWS S3 Docs
    2. Google Cloud Storage (GCS)
    3. Local FileSystem Docs

πŸ§ͺ Quickstart (UI + Docker)

OLake UI is a web-based interface for managing OLake Go jobs, sources, destinations and configurations. You can run the entire OLake Go stack (UI, Backend, and all dependencies) using Docker Compose. This is the recommended way to get started. Run the UI, connect your source DB, and start syncing in minutes.

curl -sSL https://raw.githubusercontent.com/datazip-inc/olake-ui/master/docker-compose.yml | docker compose -f - up -d

Access the UI:

Detailed getting started using OLake UI can be found here.

olake-ui

Creating Your First Job

With the UI running, you can create a data pipeline in a few steps:

  1. Configure Source: Navigate to Source tab and click Create Source. Set up your source connection.
  2. Configure Destination: Navigate to Destination tab and click Create Destination. Set up your destination.
  3. Create a Job: Navigate to the Jobs tab and click Create Job.
  4. Configure & Run: Give your job a name, set a schedule, select your source and destination and click Next to finish.
  5. Select Streams: Choose which tables to sync and configure their sync mode (CDC, Full Refresh or Incremental).

For a detailed walkthrough, refer to the Jobs documentation.


πŸ› οΈ CLI Usage (Advanced)

For advanced users and automation, OLake Go's core logic is exposed via a powerful CLI. The core framework handles state management, configuration validation, logging, and type detection. It interacts with drivers using four main commands:

  • spec: Returns a render-able JSON Schema for a connector's configuration.
  • check: Validates connection configurations for sources and destinations.
  • discover: Returns all available streams (e.g., tables) and their schemas from a source.
  • sync: Executes the data replication job, extracting from the source and writing to the destination.
  • clear-destination : Clears data in the destination, only for the selected streams defined in streams.json.

Find out more about CLI here.


Install OLake Go

Below are other different ways you can run OLake Go:

  1. OLake Go UI (Recommended)
  2. Kubernetes using Helm
  3. Standalone Docker container
  4. Airflow on EC2
  5. Airflow on Kubernetes

Playground

  1. OLake Go + Apache Iceberg + REST Catalog + Presto
  2. OLake Go + Apache Iceberg + AWS Glue + Trino
  3. OLake Go + Apache Iceberg + AWS Glue + Athena
  4. OLake Go + Apache Iceberg + AWS Glue + Snowflake
  5. OLake Go + Apache Iceberg + REST Catalog + Spark

🌍 Use Cases

  • βœ… Migrate from OLTP to Iceberg without Spark or Flink
  • βœ… Enable BI over fresh CDC data using Athena, StarRocks, Trino, Presto, Dremio, Databricks, Snowflake and more!
  • βœ… Build near real-time data lake-house on cost-efficient cloud object stores
  • βœ… Move away from vendor-lock-in warehouse or tools with open data lake-house
  • βœ… Single copy for both analytics & machine learning

🧭 Roadmap Highlights

  • Oracle Full Load Support
  • Oracle Incremental
  • Filters for Full Load and Incremental
  • Interoperability (Coming Soon)
  • Iceberg V3 Support

🀝 Contributing

We ❀️ contributions, big or small!

Check out our Bounty Program. A huge thanks to all our amazing contributors!

Documentation ΒΆ

Index ΒΆ

Constants ΒΆ

This section is empty.

Variables ΒΆ

This section is empty.

Functions ΒΆ

func RegisterDriver ΒΆ

func RegisterDriver(driver abstract.DriverInterface)

Types ΒΆ

This section is empty.

Directories ΒΆ

Path Synopsis
drivers
db2 module
google-sheets module
hubspot module
kafka module
mongodb module
mssql module
mysql module
oracle module
postgres module
s3 module
pkg
objstorage
Package objstorage provides a storage-agnostic abstraction over bucket-scoped object stores (AWS S3 and S3-compatible services today; GCS/Azure later).
Package objstorage provides a storage-agnostic abstraction over bucket-scoped object stores (AWS S3 and S3-compatible services today; GCS/Azure later).
objstorage/s3client
Package s3client builds AWS S3 clients shared by the S3 source driver (pkg/objstorage) and S3 job storage (utils/s3).
Package s3client builds AWS S3 clients shared by the S3 source driver (pkg/objstorage) and S3 job storage (utils/s3).
tests
testutils module
errs
Package errs carries a failure classification alongside an error, so telemetry can report why a run failed without shipping customer data: categories and codes are constants in this repo.
Package errs carries a failure classification alongside an error, so telemetry can report why a run failed without shipping customer data: categories and codes are constants in this repo.
s3
spec
uischema is used to serve the UI specifications of the jsonschema of all the drivers and destinations
uischema is used to serve the UI specifications of the jsonschema of all the drivers and destinations

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