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#timeseriesdata — Public Fediverse posts

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  1. Every #TimeSeriesDatabase is just a set of storage decisions:
    ➡️ Row layout
    ➡️ Compression timing
    ➡️ Partitioning strategy

    These choices often impact cost and query performance more than the database you pick.

    This #InfoQ article breaks down these fundamentals from first principles using #PostgreSQL & #ApacheParquetbit.ly/4fkDHlV

    #BigData #TimeSeriesData #Database

  2. Every is just a set of storage decisions:
    ➡️ Row layout
    ➡️ Compression timing
    ➡️ Partitioning strategy

    These choices often impact cost and query performance more than the database you pick.

    This article breaks down these fundamentals from first principles using & bit.ly/4fkDHlV

  3. How #Netflix boosted #ApacheDruid performance: by implementing interval-aware caching, they now serve 84% of analytics results from cache and have reduced query load by 33%.

    The secret? Decomposing rolling window queries into reusable time segments.
    ✅ Reduces scan volume
    ✅ Improves P90 latency
    ✅ Optimizes real-time analytics

    Details on #InfoQ: bit.ly/4uHG4DE

    #SoftwareArchitecture #DistributedSystems #DataAnalytics #TimeSeriesData #Caching #BigData #DataEngineering

  4. How boosted performance: by implementing interval-aware caching, they now serve 84% of analytics results from cache and have reduced query load by 33%.

    The secret? Decomposing rolling window queries into reusable time segments.
    ✅ Reduces scan volume
    ✅ Improves P90 latency
    ✅ Optimizes real-time analytics

    Details on : bit.ly/4uHG4DE

  5. Ever heard about SaQC, a software tool for reproducible #quality control of #timeseriesdata developed at @ufz? Here is what #wikidata knows about it: wikidata.org/wiki/Q128228853

  6. Ever heard about SaQC, a software tool for reproducible #quality control of #timeseriesdata developed at @ufz? Here is what #wikidata knows about it: wikidata.org/wiki/Q128228853

  7. Grafana Mimir 3.0 is now live!

    This release introduces a new design that cleanly separates read & write operations, delivering significant gains in performance, reliability, and cost efficiency for organizations managing metrics at scale.

    Dive into the details and explore what’s new: bit.ly/4rqnD5G

    #InfoQ #DevOps #TimeSeriesData #Observability #Grafana

  8. Grafana Mimir 3.0 is now live!

    This release introduces a new design that cleanly separates read & write operations, delivering significant gains in performance, reliability, and cost efficiency for organizations managing metrics at scale.

    Dive into the details and explore what’s new: bit.ly/4rqnD5G

  9. Deep dive into #Netflix’s Distributed Counter Abstraction - a scalable service that tracks user interactions, feature usage, and business performance metrics with low latency globally.

    “At Netflix, our counting use cases include tracking millions of user interactions, monitoring how often specific features or experiences are shown to users, and counting multiple facets of data during A/B test experiments, among others.”

    Learn more: bit.ly/49tO41Z

    #InfoQ #CaseStudy #DistributedSystems #EventsDrivenArchitecture #TimeSeriesData

  10. Deep dive into ’s Distributed Counter Abstraction - a scalable service that tracks user interactions, feature usage, and business performance metrics with low latency globally.

    “At Netflix, our counting use cases include tracking millions of user interactions, monitoring how often specific features or experiences are shown to users, and counting multiple facets of data during A/B test experiments, among others.”

    Learn more: bit.ly/49tO41Z

  11. CrateDB is designed to effortlessly manage your time-series data⌛️

    Want to learn more? Head over to our solutions page and discover why CrateDB is a perfect fit for time series💡 hubs.ly/Q01_qtsS0

  12. CrateDB is designed to effortlessly manage your time-series data⌛️

    Want to learn more? Head over to our solutions page and discover why CrateDB is a perfect fit for time series💡 hubs.ly/Q01_qtsS0

    #db #data #database #CrateDB #TimeSeriesData #DataManagement #SQLDatabase

  13. Very excited to share that I'll be speaking at :postgresql: in less than a week! I'll be announcing the new for time series and of internal .

    Bonus talk: "Don't Do This" - PostgreSQL bad practices and pitfalls!
    👇
    2023.pgdaychicago.org/

  14. Very excited to share that I'll be speaking at #PGDay #Chicago :postgresql: in less than a week! I'll be announcing the new #PostgreSQL #extension #pg_statviz for time series #analysis and #visualization of #Postgres internal #statistics.

    Bonus talk: "Don't Do This" - PostgreSQL bad practices and pitfalls!
    👇
    2023.pgdaychicago.org/

    #timeseries #timeseriesdata #opensource #database #databases #stats #performance #event #events

  15. In our next Speaker Spotlight, we meet Lana Brindley and Steve Kowalik.

    Lana lives with , and together, they set out to ask: why is it so hard to access , generated by her own body, using ?

    2023.everythingopen.au/schedul

  16. In our next #EverythingOpen Speaker Spotlight, we meet Lana Brindley and Steve Kowalik.

    Lana lives with #diabetes, and together, they set out to ask: why is it so hard to access #timeseriesdata, generated by her own body, using #OpenSource?

    2023.everythingopen.au/schedul

  17. Did you miss last week's webinar?👀

    Watch the recording now to start leveraging time-series data for your business success🚀👇

    In this webinar, you’ll gain expert insights on time-series data analysis and learn the crucial data modeling decisions needed to implement time-series data in CrateDB 👩🏻‍💻
    crate.io/resources/webinars/lp

  18. Did you miss last week's webinar?👀

    Watch the recording now to start leveraging time-series data for your business success🚀👇

    In this webinar, you’ll gain expert insights on time-series data analysis and learn the crucial data modeling decisions needed to implement time-series data in CrateDB 👩🏻‍💻
    crate.io/resources/webinars/lp

    #crateio #cratedb #db #database #webinar #recording #livedemo #data #database #datascience #timeseries #timeseriesdata #timeseriesanalysis #dataanalysis

  19. Working with time-series data in ClickHouse introduces date/time types, querying, counters & gauge metrics, codecs, materialised views, and scaling.

    All the information, in one place. Why use a time-series DB when you have ClickHouse?

    clickhouse.com/blog/working-wi

  20. Working with time-series data in ClickHouse introduces date/time types, querying, counters & gauge metrics, codecs, materialised views, and scaling.

    All the information, in one place. Why use a time-series DB when you have ClickHouse?

    clickhouse.com/blog/working-wi

    #timeseriesdata #timeseriesdb #timeseriesdatabase #clickhouse #db