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Timescale

Extend PostgreSQL for time-series data with automatic partitioning, scalable ingestion, and advanced analytics for mission-critical applications.

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Repository details:
  • Stars

    16,923
  • Forks

    857
  • Last commit

    21 hours ago
View Repository
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Timescale is a powerful open-source database built on PostgreSQL, designed to handle time-series data at scale. It combines the reliability and ecosystem of PostgreSQL with specialized features for time-series workloads, making it ideal for a wide range of applications.

Key benefits of Timescale include:

  • Seamless scalability: Automatically partition and distribute time-series data across multiple nodes, enabling effortless scaling from gigabytes to petabytes.
  • High-performance ingestion: Achieve rapid data ingestion rates, allowing you to handle millions of data points per second with ease.
  • Advanced time-series analytics: Leverage built-in functions and features optimized for time-series analysis, including continuous aggregates, data retention policies, and gap filling.
  • SQL compatibility: Utilize the full power of SQL and PostgreSQL extensions while benefiting from time-series optimizations.
  • Flexible data model: Store and query both time-series and relational data in a single database, simplifying your infrastructure.
  • Cloud-native architecture: Deploy Timescale on-premises or in the cloud, with support for containerized environments and Kubernetes.
  • Active community and enterprise support: Benefit from a vibrant open-source community and optional enterprise-grade support for mission-critical deployments.

Whether you're working on IoT applications, financial analytics, monitoring systems, or any project involving time-stamped data, Timescale provides the tools and performance you need to build scalable, reliable, and efficient time-series applications.

Repository details:
  • Stars

    16,923
  • Forks

    857
  • Last commit

    21 hours ago
View Repository
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