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DBMS > TimescaleDB

TimescaleDB System Properties

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Editorial information provided by DB-Engines
DescriptionA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Rank#83  Overall
#5  Time Series DBMS
Technical documentationdocs.timescale.com
Initial release2017
Current release2.6.0, February 2022
License infoCommercial or Open SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC
Server operating systemsLinux
Data schemeyes
Typing infopredefined data types such as float or datenumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.yes
Secondary indexesyes
SQL infoSupport of SQLyes infofull PostgreSQL SQL syntax
APIs and other access methodsADO.NET
native C library
streaming API for large objects
Supported programming languages.Net
Java infoJDBC
Server-side scripts infoStored proceduresuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Partitioning methods infoMethods for storing different data on different nodesyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integrityyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID
Concurrency infoSupport for concurrent manipulation of datayes
Durability infoSupport for making data persistentyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlfine grained access rights according to SQL-standard
More information provided by the system vendor
Specific characteristics

Timescale is the creator of TimescaleDB, the first open-source relational database for time-series data. TimescaleDB offers the reliability, flexibility, ease-of-use, and scalability that applications, data analytics infrastructure, and complex systems require. 

All data is time-series dataTime-series data captures how information changes over time - website and infrastructure performance, financial tick data, and more - and TimescaleDB is the only relational database built with the performance, scalability, and reliability to store these relentless streams of data.

Timescale offers TimescaleDB as a hosted service through Timescale Cloud. Developers choose Timescale Cloud for many reasons, including:

  • Worry-free operations. Hosted and managed by Timescale, freeing teams to focus on running their business and analyzing data, not managing data infrastructure. 

  • Complete flexibility. Scale your services in one click, with decoupled compute and storage pricing.

  • Get started quickly. Launch your database in seconds, including multi-node services.

TimescaleDB at-a-glance

Supercharged Postgres

  • Full SQL, no restrictions

  • Rock-solid reliability and scalability

  • Compatible with a vast ecosystem of extensions and tools

Accelerated Performance

  • Get 10X faster inserts, 1,400X faster queries, and ingest 1.5M+ more metrics per second per server

  • Speed up your aggregate queries to get real-time insights with continuous aggregates

  • Downsample your dataset automatically to do fast analysis over historical data

Massive scale

  • Store 100s of billions of rows & 10s of TBs of data per server

  • Best-in-class datatype-specific compression algorithms for 16x storage capacity

  • Create multi-node databases with distributed hypertables across many TimescaleDB nodes

Relational and time-series, together

  • Correlate your time-series and business data

  • Perform JOINs to understand relations with time-series

  • Ensure clean, correct data with foreign keys and constraints

Worry-free operations

  • Spin up a pre-configured instance in seconds

  • Automated, continuous backups with point-in-time recovery

  • Integrated metrics, logs, security and user controls 

Lower costs

  • Reduce storage costs with 94-97% lossless compression rates

  • Decoupled storage and compute pricing

  • Scale compute and storage in one click according to your needs

To get started, check out the Timescale Docs and the Timescale Slack Community.

Competitive advantages

TimescaleDB is purpose-built to scale and handle time-series data workloads and is intentionally designed as a PostgreSQL extension. Its features include:

  • Native support for ANSI SQL, including JOINs with relational metadata that can be stored right in standard PostgreSQL tables
  • time_bucket and gap_fill, allowing users to query data at any time interval (v. SQL limitations) and choose how they solve for NULL values and missing data
  • GIS support (via PostGIS, another PostgreSQL extension) to roll your own geo-temporal database
  • Support for ACID operations and transactions 
  • Secondary indexes, including composite indexes
  • Secondary JOINs
  • Transparent resource utilization and performance (e.g. many options for administration and tooling, offers the ability to run EXPLAIN, etc.)
  • Native compression and real-time aggregation capabilities to reduce data stored on disk, while still allowing users to analyze historical data
  • Automated data retention policies to remove the burden of manual data lifecycle management
  • Integration with Grafana and Prometheus for data visualization and long-term data storage (roll your own IT Monitoring stack)

TimescaleDB combines the reliability and tooling of PostgreSQL with enterprise-grade security, production-ready SLAs, and community-based and professional support services. 

TimescaleDB is also flexible and customizable, supporting thousands of extensions, products, and integrations critical for data analysis, including: Tableau, Looker, Mode, Grafana, PowerBI, Apache Kafka, RabbitMQ, Apache Spark, Prometheus, Zabbix, JDBC/ODBC, Telegraf, and more.

Typical application scenarios

Time-series Analytics

TimescaleDB boosts the performance of PostgreSQL for time-series data, giving you significantly higher inserts and faster queries so you can drive real-time, user-facing dashboards for your data-intensive applications. On top of it, TimescaleDB expands SQL for time-series. Use hyperfunctions like time_bucket, gap_fill, or stats_agg  to easily do complex analysis in SQL, define continuous aggregates to speed up your aggregate queries over high data volumes, and combine compression with data retention policies to automatically and progressively downsample your data once it reaches a certain age. 

 Internet of Things

Device and sensor data are time-series data: tracking device performance with pinpoint geospatial and temporal accuracy is a time-series problem. TimescaleDB helps you cost-effectively store and analyze relentless streams of device telemetry and sensor readings at scale, in order to manage industrial equipment maintenance, fleet management, asset tracking, route planning, yield optimization, oil and gas production, and more.

 Web3 + Crypto

Whether you are analyzing the price of cryptocurrencies, tracking NFT sales, or monitoring blockchains, you are working with time-series data. Thanks to its combination of excellent ingestion and real-time capabilities with the ability to do historical data analysis, TimescaleDB is an optimal choice for web3 use cases. Features like time_bucket, continuous aggregates, and compression make it quick and easy to do complex analysis in SQL, while ingesting thousands of data points per second to feed real-time dashboards, and keeping the storage costs low. 

​ Observability

Observability data is time-series data. By using Promscale, the observability backend built on PostgreSQL and TimescaleDB, you can seamlessly store Prometheus metrics and OpenTelemetry traces in TimescaleDB. This allows you to use SQL to analyze your observability data, getting unprecedented insights about your systems. Plus, can leverage features like compression, contintinuous aggregates, and data retention policies to automatically reduce your data volume and save storage costs, enjoy full compatibility with open source tools like Grafana and Jaeger, and the rock-solid reliability of PostgreSQL.

Key customers

TransferWise, Maersk, Walmart, Comcast, LaunchDarkly, IBM, NOV, Cisco, Nutanix, Warner Music Group, Bosch, Uptake, Samsung, Northvolt, Siemens, Schneider Electric, Attentive, Zabbix, Ambient.ai, Embark, FlipsideCrypto, Nightfall, Charter Communications, and more.

Market metrics

With over 12,700 GitHub stars and growing, 1,000,000 active databases, and an active Slack community, TimescaleDB is trusted by developers and teams around the world.

Licensing and pricing models

TimescaleDB is available as a self-hosted product under two licenses, the Timescale License (TSL) and the Apache 2 License. Both versions of TimescaleDB are completely free to use. For more information on Timescale’s licensing, click here.

For those looking to run TimescaleDB as a hosted product in the cloud, Timescale offers two options, Timescale Cloud and Managed Service for TimescaleDB. Timescale Cloud is a cloud platform owned and developed exclusively by Timescale, while Managed Service for TimescaleDB is operated by Timescale in partnership with Aiven.  For more information about Timescale’s hosted options and pricing, click here

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Recent citations in the news

Timescale Announces OpenTelemetry Tracing Support for Promscale
16 May 2022, Business Wire

Timescale launches the new Timescale Cloud, a hosted relational database for time-series
5 October 2021, Business Wire

Understanding Hyperfunctions in TimescaleDB
11 August 2021, CDOTrends

Timescale Valuation Rockets to Over $1B with $110M Round, Marking the Explosive Rise of Time-Series Data
22 February 2022, Business Wire

How time series platforms unlock the potential of IoT: Join theCUBE for May 17 event
10 May 2022, SiliconANGLE News

provided by Google News

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