Many real-world processes produce information as a steady stream moderately than as remoted data. Sensor readings, monetary markets, and software telemetry all generate information this manner. This type of time-series information has a particular form. It’s written much more usually than it’s up to date, it accumulates repeatedly, and it’s often queried throughout ranges of time. Time-series databases are constructed particularly for this sort of workload.
TimescaleDB is an open supply database from Tiger Knowledge that provides time-series capabilities to PostgreSQL. It’s carried out as a Postgres extension, so it introduces new performance whereas preserving normal Postgres conduct and SQL. This lets a single Postgres-based system deal with each transactional and analytical workloads with out splitting information throughout a number of instruments.
Brandon Purcell is the Director of Product Administration at Tiger Knowledge. On this episode, Brandon joins Kevin Ball to debate why time-series information breaks typical databases, how hypertables and Hypercore scale Postgres, zero-copy database forking for agent-based workflows, and rather more.
Full Disclosure: This episode is sponsored by Tiger Knowledge
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