May 2019 Summaries

Watch the webinar recording to learn more about storing, querying, and analyzing time-series data. Microsoft Azure Database for PostgreSQL is an enterprise-ready managed database service, powered by PostgreSQL, which makes it easy to store and query time-series data with TimescaleDB. During the webinar, we discussed what time-series data is, why it's so important for IoT applications, and how TimescaleDB helps you efficiently and effectively store and query time-series data. We also demonstrated how you can analyze time-series data with Azure IoT Hub and Azure Functions to power your IoT applications. The integration of TimescaleDB and Azure Database for PostgreSQL is available now, and the Timescale team is ready to help with any questions or issues. You can find more information on our partnership with Microsoft Azure, as well as resources to learn more about TimescaleDB and Azure Database for PostgreSQL.

TimescaleDB 1.3 introduces automated continuous aggregates, which can massively speed up workloads that need to process large amounts of data by automatically maintaining the results from a query and allowing users to retrieve them as they would any other data. Continuous aggregates are created like regular views but do not perform the average when queried, unlike materialized views, and their refresh is automatic in the background as new data is added or old data is modified. This feature is unique to TimescaleDB, which tracks previous data updates and delays data points, ensuring that continuous aggregates can be recomputed on older data without slowing down INSERT operations. The system consists of a materialization hypertable, a query engine, an invalidation engine, and a materialization engine, all designed to ensure good performance. Continuous aggregates work with various built-in aggregate functions, including averages, counts, and sums, and users can define their own custom aggregation functions as long as they are parallel-safe.