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CrateDB allows ingesting large amounts of data, from hybrid sources and at scale, while allowing real-time queries with a familiar SQL interface. With the release of CrateDB v4.6 we continue to improve CrateDB to achieve these goals even better, based on our customer and user feedback.
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In this tutorial, we show you how to export your tables from PostgreSQL/TimescaleDB and import them into CrateDB.
Apart from including the Enterprise features and new statements as the CREATE TABLE AS, with CrateDB v4.5 we've done work behind the scenes—with improvements in the documentation, error messages, and stability.
SQL is a powerful language for analyzing time series data. In this blogpost, we teach you some queries using the NYC taxi dataset and CrateDB Cloud.
You can now sign up for a CrateDB Cloud free trial! Use a 3-node cluster for 14 days, with 96 GB of storage and up to 600 ingests per second.
In this release, we improved the performance and stability of CrateDB, diagnostics, and its standard SQL and Postgres compatibility.
In this release, the CrateDB team has focused on improving speed in aggregations, SQLcompatibility and usability.
In this blog post, we compare how MongoDB, TimescaleDB, InfluxDB, and CrateDB perform for an industrial IoT use-case.
CrateDB 4.1 adds support for more SQL features that support time series use-cases, including interval-based data management. We also improved string scalars.
You don't have to choose between operational historians or a time-series database for industrial IoT. There's a third option.
