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A Time-Series Database in Postgres - WHY?
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In this episode of Simplyblock's Cloud Commute Podcast, host Chris Engelbert interviews Mike Freedman, co-founder and CTO of Timescale. Timescale enhances Postgres to manage time series data, analytics, and AI applications efficiently. Mike explains how Timescale's automated partitioning and lifecycle management transform data from row-based to compressed columnar formats and tiered storage, optimizing performance, and cost. The episode dives into Timescale’s use of Kubernetes for scalable, decoupled compute and storage, ensuring seamless high availability and efficient resource management, alongside addressing challenges of stateful database management in Kubernetes environments.
If you want to reach out to Mike or Timescale, here's your chance:
- LinkedIn: https://www.linkedin.com/in/mfreed/
- X/Twitter: https://x.com/michaelfreedman
- Timescale Website: http://timescale.com/
- Timescale LinkedIn: https://www.linkedin.com/company/timescaledb/
- Timescale X/Twitter: https://x.com/TimescaleDB
- Free Trial Signup: https://console.cloud.timescale.com/signup
Additional Show Notes:
- Get Started Guide: https://docs.timescale.com/getting-started/latest/
- What is Time Series Data: https://www.timescale.com/blog/time-series-introduction/
- What is Time Series Forecasting: https://www.timescale.com/blog/what-is-time-series-forecasting/
- Time Series (Wikipedia): https://en.wikipedia.org/wiki/Time_series
- PostgreSQL: https://www.postgresql.org/
- pgvector: https://github.com/pgvector/pgvector
- pgvectorscale: https://github.com/timescale/pgvectorscale
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