Postgres extended for time-series. Millions of writes, millisecond queries
Hypercore, Continuous Aggregates, and 100+ Hyperfunctions help you store, analyze, and act on time- series data at any scale
Massive ingest, instant queries, 95% less storage
Millions
Rows per second ingest
350x
Faster analytical queries than vanilla postgres
95%
Compression, saving you money
Launch your time-series native Postgres today
From ingest to insight in a heartbeat
TigerData streams millions of rows per second into a hypertable, rolls them up with Continuous Aggregates, and serves real-time queries through a vectorized columnstore—all in standard SQL. No shards to manage, no new query language to learn; just plug Grafana in and watch fresh metrics render in < 100 ms.
- 562,333 rows/s sustained ingest
- 350 × faster scans with Hypercore
- 95% compression & tiered storage
Columnar speed, row simplicity
Dashboards stay real-time
Analytics—pure SQL, no ETL
Auto-compression
Shrink cold chunks by 95% with one command; Storage costs drop, queries stay fast.
Smart retention
Setting a retention policy prunes obsolete rows on schedule—no cronjobs, no batch scripts—keeping hot data lean and cacheable.
Tiered storage
Age old partitions out to cheap object storage without losing SQL access. Same table, lower bill.
Observability ready
Native PromQL adapter and pg-exporter metrics mean TigerData drops into your existing Grafana stack.
High availability
Multi-AZ clusters with synchronous replicas deliver < 30 s failover; nothing new to learn—it’s still Postgres.
Open-source freedom
Apache-2.0 core, cloud when you want convenience. Migrate in either direction with standard pg_dump.