Tiger Cloud is a managed PostgreSQL time-series database built for high-ingest, long-retention telemetry across EV charging networks, battery storage fleets, renewable assets, and grid platforms.
Retention stretches from weeks to years for compliance and reporting. Fleet dashboards slow down. Infrastructure costs rise. Engineering teams get stuck rebuilding the data layer instead of shipping product.
Common breaking points:
InfluxDB struggles as queries and joins get more complex
Amazon Timestream is no longer open to new customers
MongoDB is not built for high-ingest time-series workloads
Vanilla PostgreSQL requires heavy engineering at scale
Tiger Cloud is built for operational telemetry from day one.
High-ingest time-ordered telemetry from chargers, meters, and storage systems.
High ingest. Long retention. Predictable cost
90%+ compression for cost-effective multi-year retention
Automatic time-based partitioning for fast fleet and portfolio queries
Fast SQL across real-time and historical asset data
High availability for operational systems
Full PostgreSQL compatibility
No new query language. No pipeline sprawl
Ingest millions of time-ordered readings from chargers, meters, and grid assets
Tiger Cloud powers operational telemetry across electrified infrastructure:
01
EV charging fleet telemetry and charger analytics
02
Battery storage monitoring and grid-scale energy systems
03
Renewable asset monitoring for solar and wind fleets
04
Grid software and DERMS platforms
05
Energy trading built on operational asset data
06
Emissions monitoring and regulatory reporting
NextEra Energy
Runs multiple operational telemetry workstreams on Tiger Cloud.
Octave Energy
Replaced Timestream and built real-time dashboards.
Easee
Cut storage costs after migrating from Aurora.
Flogistix
Monitors oilfield systems with always-on telemetry.
Run in the cloud, on-prem, or at the edge using just Postgres.