Event Ingestion Pipeline With Dual Write To Postgresql And Clickhouse

via “event ingestion pipeline with dual-write to postgresql and clickhouse”

Open-source LLM observability — tracing, prompt management, evaluation, cost tracking, self-hosted.

Unique: Dual-write architecture separates transactional (PostgreSQL) and analytical (ClickHouse) concerns, enabling real-time trace queries on PostgreSQL while ClickHouse handles aggregations on billions of events. Event enrichment and masking are applied before persistence, ensuring that stored data is clean and compliant.

vs others: More scalable than single-database approaches because ClickHouse columnar storage enables sub-second aggregations on 100M+ events, whereas PostgreSQL would require expensive full-table scans. Dual-write ensures transactional consistency for trace reconstruction while maintaining analytical performance.

via “analytics and event tracking with clickhouse time-series database”

Open-source computer vision annotation tool.

Unique: Uses ClickHouse (columnar time-series database) instead of traditional relational databases, enabling fast aggregation queries without impacting operational performance. Events are immutable and append-only, providing reliable audit trails.

vs others: More performant than querying PostgreSQL for analytics (which requires expensive joins) and more scalable than in-memory analytics (which requires large memory footprint). ClickHouse is purpose-built for time-series analytics.