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## OLake Community Call #9

Introducing Kafka-Powered CDC Pipelines and Smarter Ingestion Controls Across the Open Lakehouse
​In our previous community call, we explored real-world CDC challenges, showcased Oracle support, incremental syncs, ingestion filters, and Helm-based deployments, demonstrating how OLake simplifies open lakehouse operations end to end.
​For our 9th community meetup, we’re introducing the next wave of advancements expanding OLake’s CDC ecosystem and refining user control, performance, and reliability.
1. Expanding with Kafka Support
​This update brings Kafka support, enabling data ingestion from Kafka topics directly into Iceberg.
It supports batch data ingestion ideal for modern architectures and will be demonstrated live during the community call.
2. Smarter Sync Management

  • Clear Destination: Erases all data from the destination for a particular job, simplifying reconfiguration and cleanup.
  • Cancel Job: Safely stop running syncs while preserving checkpoints for consistent recovery.
  • Flexible Ingestion Modes: Choose between Append for ingesting all records or Upsert for keeping only the latest updates.

3. Simplified Iceberg Destination Handling

  • Table/Column Normalization: Table and column names are normalized to ensure compatibility with tools like AWS Glue and others that don’t support uppercase letters or special characters.
  • Destination Database & Namespace Options:
    When a job is created and streams are discovered, Olake automatically creates a destination database to store synced tables. You can choose between per-namespace or a unified database setup ensuring seamless compatibility across Trino, Athena, and Iceberg.

4. Secure Connectivity

  • IAM Integration for MongoDB: Passwordless AWS IAM-based authentication, reducing credential management and improving compliance.

5. Documentation & Learning
​We’ve revamped the documentation to make contributing and experimenting easier than ever.
A new set of blogs around Apache Iceberg and tutorials with Polaris and Bauplan highlight adoption patterns and practical workflows across open lakehouse stacks.
6. Community Spotlight
​We’ll wrap up with a community spotlight, celebrating contributions from our Hacktoberfest participants and ongoing open-source efforts.
From PRs to discussions, our contributors continue to drive the wave toward a more open, collaborative, and high-performance data ecosystem.

Big Data
Data Engineering
Data Management
Database Professionals

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