TimescaleDB - Timeseries database for PostgreSQL
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Building columnar compression in a row-oriented database
Engineering

Building columnar compression in a row-oriented database

How we achieved 91%-96% compression in the latest version of TimescaleDB

  • Mike Freedman
    Mike Freedman
14 min read
Building a distributed time-series database on PostgreSQL
Engineering

Building a distributed time-series database on PostgreSQL

Today we are announcing the distributed version of TimescaleDB, which is currently in private beta (public version slated for later this year).

  • Mike Freedman
    Mike Freedman
  • Erik Nordström
    Erik Nordström
17 min read
TimescaleDB vs. InfluxDB: Purpose built differently for time-series data
Product

TimescaleDB vs. InfluxDB: Purpose built differently for time-series data

An in-depth look into how two leading time-series databases stack up in terms of data model, query language, reliability, performance, ecosystem, operational management, and company/community support.

  • Mike Freedman
    Mike Freedman
24 min read
TimescaleDB 1.2: Analytical functions, automated data lifecycle management, improved performance, and more
Product

TimescaleDB 1.2: Analytical functions, automated data lifecycle management, improved performance, and more

Milestone release includes open-source improvements as well as our first community and enterprise features

  • Mike Freedman
    Mike Freedman
6 min read
TimescaleDB 1.0 is production ready
Product

TimescaleDB 1.0 is production ready

Since announcing our first release candidate in September, Timescale’s engineering team has merged over 50 PRs to harden the database, improving stability and ease-of-use.

  • Mike Freedman
    Mike Freedman
5 min read
Time-series data: Why (and how) to use a relational database instead of NoSQL
Engineering

Time-series data: Why (and how) to use a relational database instead of NoSQL

These days, time-series data applications (e.g., data center / server / microservice / container monitoring, sensor / IoT analytics, financial data analysis, etc.) are proliferating.

  • Mike Freedman
    Mike Freedman
14 min read
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