Companies that trust Timescale.
TimescaleDB’s continuous aggregations changed our dashboards from sluggish to lightning fast. It used to take minutes to run some long-term data queries. Now, almost all queries for long-term data are sub-second.
Jon Eskilsson, Software Architect at Edeva
Energy insights, reliable and fast
Store energy generation/consumption data from hundreds of thousands of devices.
Efficiently handle high write rates from all monitored assets.
Rely on blazingly fast energy dashboards even when your tables have billions of rows—all without hurting your ingest.
Analyze and optimize your electrical grid, batteries, solar panels, and other devices according to the data received in real time.
Seamless scaling to handle data growth
Accommodate larger data sets, handle higher data ingestion rates, and easily support a growing number of concurrent users or devices.
Automatic data retention policies, compression, and data partitioning ensure efficient utilization of storage resources while maintaining query performance.
Lower data storage costs up to 10x via data tiering to Amazon S3 and 90+% native compression rates.
PostgreSQL with time-series superpowers
For faster reads and write, take advantage of automatic time-based partitioning with hypertables.
Use pre-calculated continuous aggregates to accelerate queries requiring aggregated results by time interval or range.
Streamline your development with pre-built functions that easily integrate into your energy applications.
Access to expert support
Get a second opinion on your database setup when you need it—at no extra cost to you.
Always on, without additional charges
We are available 24 x 7 x 365 to ensure that you have a lifeline when unexpected events happen.
Guided every step, never walk alone
Get assistance with migrations, data modeling, query or ingest performance, compression settings, and more.
Tailored solutions for your unique needs
When it comes to data, there is no one-size-fits-all strategy. We work with you to create a solution to meet your specific circumstances.
“[Timescale] was great for storing time-series data and enabled us to do a lot of analytical work. The most important thing for me is that mixing model and time-series data enhances our platform’s analytical power.”
Xavier Orduña, Platform team lead at Circutor
Learn how developers building energy apps use Timescale in production and start building with tutorials and real-world datasets.
How Octave Achieves a High Compression Ratio and Speedy Queries on Historical Data While Revolutionizing the Battery Markett
How Ndustrial Is Providing Fast Real-Time Queries and Safely Storing Client Data With 97% Compression
How I Am Planning My Photovoltaic System Using Timescale
Calculating energy use from instantaneous power usage measurements (transforming kW to kWh)
Measuring Deltas Correctly for Smart Energy Meters
Understanding general trends of the energy usage with hyperfunctions
Using IoT Sensors, Timescale, and Grafana to Control the Temperature of the Nuclear Fusion Experiment at the Max Planck Institute