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TimescaleDB

PostgreSQL for time-series.

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Overview

TimescaleDB is an open-source time-series database that is packaged as a PostgreSQL extension. It is designed to make PostgreSQL scalable for time-series data while retaining the reliability, ecosystem, and SQL interface of PostgreSQL. TimescaleDB automatically partitions data by time and provides other features to optimize for fast ingest and complex queries on time-series data.

✨ Key Features

  • Built on PostgreSQL
  • Automatic time-based partitioning (hypertables)
  • Full SQL support
  • High data ingestion rates
  • Data compression
  • Continuous aggregations

🎯 Key Differentiators

  • Built on PostgreSQL, providing reliability and a rich ecosystem
  • Full SQL support
  • Combines the benefits of relational and time-series databases

Unique Value: TimescaleDB provides the scalability and performance of a time-series database with the reliability and familiarity of PostgreSQL.

🎯 Use Cases (5)

Monitoring and observability IoT data analysis Financial data analysis Fleet management Application performance monitoring

✅ Best For

  • Monitoring at Comcast
  • IoT platform at Bosch
  • Financial analytics at a major bank

💡 Check With Vendor

Verify these considerations match your specific requirements:

  • Non-time-series data
  • Graph data

🏆 Alternatives

InfluxDB Prometheus ClickHouse

Unlike other time-series databases that use proprietary query languages, TimescaleDB's full SQL support makes it easier for developers to get started and leverage their existing skills.

💻 Platforms

Linux macOS Windows Docker Kubernetes API

🔌 Integrations

PostgreSQL ecosystem Grafana Tableau Prometheus Kafka

🛟 Support Options

  • ✓ Email Support
  • ✓ Live Chat
  • ✓ Phone Support
  • ✓ Dedicated Support (Enterprise tier)

🔒 Compliance & Security

✓ SOC 2 ✓ GDPR ✓ ISO 27001 ✓ SSO ✓ SOC 2 Type II ✓ ISO 27001

💰 Pricing

Contact for pricing
Free Tier Available

✓ 30-day free trial

Free tier: Free tier for Timescale Cloud with usage limits.

📊 Market Info

Customers: NA

Total Funding: $180.0M

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