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Software Engineering Radio - the podcast for professional software developers

SE Radio 623: Michael J. Freedman on TimescaleDB

Jul 3, 2024
01:05:43
Snipd AI
Professor Michael J. Freedman from Princeton and co-founder/CTO of Timescale, discusses TimescaleDB's history, integration with PostgreSQL, data suitability, IoT data formats, sharding, and upgrade management. They tackle challenges in managing time series data, technologies, Rust integration, collaboration with Postgres team, security contributions, and optimization strategies. Exciting conversations around TimescaleDB's capabilities and enabling developers to innovate.
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Podcast summary created with Snipd AI

Quick takeaways

  • Time series data is valuable for analyzing trends and predicting outcomes.
  • Operational databases face challenges with high data arrival rates and historical data retention.

Deep dives

Overview of Time Series Data

Time series data refers to any metric or event information collected over time, valuable for understanding past trends and predicting future outcomes. This data often exhibits patterns and is collected in regular or irregular streams, allowing businesses to analyze changes over different timeframes. Common time frames range from hourly data analysis to historical trends spanning years, with varying data access needs.

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