Optimizing writes to OLAP using buffers (ClickHouse, Redpanda, MooseStack)
6 days ago
- #DataIngestion
- #ClickHouse
- #OLAP
- OLTP databases are optimized for small, individual transactions with ACID guarantees, balancing contention and commit latency.
- OLAP databases like ClickHouse benefit from larger, well-formed inserts to reduce merge work and improve compression.
- Best practices for OLAP include batching data (e.g., 100k rows or 1s worth of data) to balance freshness and efficiency.
- Using a streaming buffer like Kafka or Redpanda before the OLAP database decouples producers and ensures durability.
- MooseStack simplifies setting up ClickHouse tables and streaming buffers with best practices for micro-batching.
- For file-oriented loads in OLAP, target ~100–512 MB compressed files and use parallel processing.