Creators of TimescaleDB
Postgres for sensor and machine data
Built for industrial, energy, and robotics systems.
Real life scale of a single TimescaleDB Instance
3 TRILLION
METRICS PER DAY
1 QUADRILLION
DATA POINTS STORED
3 PETABYTES
DATA VOLUME
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Built for the hardest workloads
The foundational capabilities that power fast ingest, efficient storage, and real-time analytics at scale.
Automatic partitioning
Time- and key-based partitioning for fast reads and writes.
Row-columnar storage
Row storage for writes, columnar storage for analytics, with compression.
Tiered storage
Hot data on SSD, colder data on low-cost object storage.
Lakehouse integration
Ingest from Kafka and S3, replicate to Iceberg.
Time-series functions
200+ SQL functions for time-based analytics.
Interface
Postgres-native access via SQL, APIs, CLI, and UI.
Search
Hybrid retrieval with keywords, vectors, filters, and ranking.
We observed significant speed-ups, from 10x to 40x, depending on the query, range, and data frequency.
science research
Our partners
From cloud infrastructure to industrial automation, Tiger Data works where your data already lives.
Integrations
Use Tiger Data with your preferred cloud provider, and the wider Postgres ecosystem.
Enterprise-ready
Meet security and operational requirements of production systems.
Secure
Encryption at rest and in transit, private networking, and access controls.
Reliable
High availability, automated backups, and point-in-time recovery.
Compliant
SOC 2 Type II, GDPR support, and enterprise security standards.