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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#97  Overall
#5  Time Series DBMS
Technical documentationdocs.timescale.com
Initial release2017
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 data. Time-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.

 Developers choose hosted TimescaleDB for many reasons:

  • 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. Deploy in any major cloud provider in 75+ regions.

  • Get started quickly. Launch your database in seconds.

TimescaleDB at-a-glance

Supercharged Postgres

  • Full SQL, no restrictions

  • Use your favorite PostgreSQL extensions

  • Connect Prometheus for all your observability metrics

  • Visualize data using the dashboards you love

Accelerated Performance

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

  • Real-time insights over automated continuous aggregations

  • Query faster over longer time horizons with downsampling

Massive scale

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

  • Best-of-breed datatype-specific compression for 16x storage capacity

  • Create distributed hypertables across many TimescaleDB nodes

Relational and time-series, together

  • Correlate metrics with business and system-of-record 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 30 seconds

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

  • Integrated metrics, logs, security and user controls 

Lower costs

  • Reduce storage costs with best-in-class compression algorithms (94-97% lossless compression rates)

  • Scale compute and storage based on changing needs

For more information about which TimescaleDB version is right for you and to get started, please view our product detail page, documentation, and join us in our active Slack Community.

Competitive advantages

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

Additionally, with fully managed (cloud), self-managed, and open source versions, developers can opt for the solution that works for their needs.

TimescaleDB is a category-defining time-series database for many reasons, including features like:

  • 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

DevOps and Infrastructure Monitoring

All monitoring data is time-series data. Efficiently finding and addressing infrastructure and application issues is a time-series problem. TimescaleDB helps you cost-effectively store and analyze data at scale to identify and predict performance anomalies and service outages, conduct post-mortems, and plan for future capacity needs. Whether you’re collecting home-grown monitoring data, Prometheus metrics, Kubernetes events, logs, or custom metrics, TimescaleDB enables you to measure what matters.

Customer and Internal-facing SaaS applications and Data Pipelines

Product data is time-series data. Quickly understanding how your product is used over time, segmenting your customer base, and making product and business decisions is a time-series problem. Or use TimescaleDB to drive user-facing dashboards and analytics when your product is time-series data. TimescaleDB can store all of your application metrics at a fraction of the cost of an analytics service. Timescale gives you all the reliability and flexibility of PostgreSQL, meaning you can use full SQL to construct queries to better understand your products and delight your users.

IoT, Industrial Machine, and Sensor Data

Device and sensor data is 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.

Financial Information

Financial data is time-series data. Understanding market and tick data accurately and combining that data with other sources of information is a time-series problem and the foundation of modern financial analysis. TimescaleDB is PostgreSQL with superpowers, meaning you can easily track your time-series tick data, order books, and other market data in a proven database with rock-solid reliability, and correlate it with other relational data.

Key customers

TransferWise, Maersk, AppDynamics, 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 9,000 GitHub stars and growing, 600,000 active databases, and an active Slack community, TimescaleDB is trusted by developers and teams around the world.

Licensing and pricing models

TimescaleDB comes in 3 versions, including fully managed Cloud-hosted solutions*, licensed under Apache 2 and Timescale License (TSL).

*Timescale offers hosted TimescaleDB options starting at $49/month.

To learn more and find the version that’s best for you, please see our product matrix here (and read more about our support options).

Related products and services
ClusterControl: the only management system you’ll ever need to take control of your open source database infrastructure.

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 Launches Industry's First Multi-Node Relational Database for Time-Series Data, Giving Organizations Unprecedented Scale
29 October 2020, Business Wire

Timescale Brings Powerful Time-Series Data Analysis to Developers Worldwide, Now Available in 75+ Cloud Regions
12 August 2020, Business Wire

TimescaleDB Delivers Another Option for Time-Series Analytics
17 October 2019, Datanami

It’s About Time For Time Series Databases
25 January 2018, The Next Platform

Timescale Database Now Available in 76 Cloud Regions
12 August 2020, Datanami

provided by Google News

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