All posts
architecture1 min read

Building Modern Lakehouses with Flink and Apache Paimon

Explore the unified stack: How PerunsCloud integrates Flink-CDC and Paimon to create a seamless real-time data lake.

Anna Nowak

Anna Nowak

Building Modern Lakehouses with Flink and Apache Paimon

The gap between "Real-time Streaming" and "Batch Analytics" is finally closing. At the heart of this revolution is the combination of Flink-CDC and Apache Paimon.

The Ingestion Powerhouse: Flink-CDC

In the past, syncing your production database with your data lake required complex ETL jobs. With our native CDC (Change Data Capture) integration, PerunsCloud streams every insert, update, and delete from your Postgres or MySQL directly into your analytics layer in sub-seconds.

The Storage Revolution: Apache Paimon

Why Paimon? Because it allows you to treat your data lake like a real-time database.

  • High Throughput: Handles massive streaming writes without breaking a sweat.
  • Unified Format: The same data is available for real-time Flink queries and long-term batch processing.
  • Acid Transactions: Reliability that was previously reserved only for traditional RDBMS.

The PerunsCloud Edge

We don't just "support" these tools; we provide them as a Unified Stack. When you provision a vNode on our platform, the integration between CDC and Paimon is pre-configured and optimized for the AWS EKS backbone.