Apache Druid is a real-time analytics database built for the datacenter era. It cannot exploit the efficiency and simplicity of the cloud, making it challenging to achieve performance at scale. Rockset is built for the cloud with compute-storage and compute-compute separation so you no longer need to overprovision resources. Save infrastructure costs and operational effort with a cloud native, fully-managed solution.
Less Compute per Query
Rockset separates storage, ingest and query compute so you don’t need to overprovision resources for your workload. Furthermore, Rockset can save up to 100x on storage costs by using SQL-based rollups.
Faster Query Performance
Rockset is 1.12 times faster than Druid with the same hardware configuration based on results from the Star Schema Benchmark (SSB).
Faster Development Time
Rockset is cloud-native, saving your team from needing to manage clusters, nodes, shards and indexes. Furthermore, Rockset’s Converged Index enables ad-hoc analytics without performance tuning so teams realize real-time analytics 20x faster.
Rockset Beats ClickHouse and Druid on the Star Schema Benchmark (SSB)
Compare real-time analytics databases in 2023: Rockset, Apache Druid, ClickHouse, Pinot
Change Data Capture: What It Is and How to Use It
Introducing Compute-Compute Separation for Real-Time Analytics
How to Handle Database Joins in Apache Druid vs Rockset
How to Handle Nested Data in Apache Druid vs Rockset
Rockset is built to exploit the efficiency of the cloud for real-time analytics, delivering consistent performance at a fraction of the cost.
Here are four reasons why:
Creation of search, columnar and row indexes at ingest time
SQL search, aggregations and joins on semi-structured data
Efficient inserts, updates and deletes
Independent scaling of storage-compute and compute-compute