Analytics Buckets
This feature is in Private Alpha. API stability and backward compatibility are not guaranteed at this stage. Reach out from this Form to request access
Analytics Buckets are designed for analytical workflows on large datasets without impacting your main database.
Postgres tables are optimized for handling real-time, transactional workloads with frequent inserts, updates, deletes and low-latency queries. Analytical workloads have very different requirements: processing large volumes of historical data, running complex queries and aggregations, minimizing storage costs, and ensuring these analytical queries do not interfere with the production traffic.
Analytics Buckets address these requirements using Apache Iceberg, an open-table format for managing large analytical datasets efficiently.
Analytics Buckets are ideal for • Data warehousing and business intelligence • Historical data archiving • Periodically refreshed real-time analytics • Complex analytical queries over large datasets
By separating transactional and analytical workloads, Supabase makes it easy to build scalable analytics pipelines without impacting your primary Postgres performance.