DBMS > TimescaleDB
TimescaleDB System Properties
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|Editorial information provided by DB-Engines|
|Description||A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL|
|Primary database model||Time Series DBMS|
|Secondary database models||Relational DBMS|
|Current release||2.6.0, February 2022|
|License Commercial or Open Source||Open Source Apache 2.0|
|Cloud-based only Only available as a cloud service||no|
|DBaaS offerings (sponsored links) Database as a Service|
Providers of DBaaS offerings, please contact us to be listed.
|Server operating systems||Linux|
|Typing predefined data types such as float or date||numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types|
|XML support Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.||yes|
|SQL Support of SQL||yes full PostgreSQL SQL syntax|
|APIs and other access methods||ADO.NET|
native C library
streaming API for large objects
|Supported programming languages||.Net|
|Server-side scripts Stored procedures||user 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 Methods for storing different data on different nodes||yes, across time and space (hash partitioning) attributes|
|Replication methods Methods for redundantly storing data on multiple nodes||Source-replica replication with hot standby and reads on replicas|
|MapReduce Offers an API for user-defined Map/Reduce methods||no|
|Consistency concepts Methods to ensure consistency in a distributed system||Immediate Consistency|
|Foreign keys Referential integrity||yes|
|Transaction concepts Support to ensure data integrity after non-atomic manipulations of data||ACID|
|Concurrency Support for concurrent manipulation of data||yes|
|Durability Support for making data persistent||yes|
|In-memory capabilities Is there an option to define some or all structures to be held in-memory only.||no|
|User concepts Access control||fine grained access rights according to SQL-standard|
|More information provided by the system vendor|
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.
Timescale offers TimescaleDB as a hosted service through Timescale Cloud. Developers choose Timescale Cloud for many reasons, including:
Relational and time-series, together
TimescaleDB is purpose-built to scale and handle time-series data workloads and is intentionally designed as a PostgreSQL extension. Its features include:
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|
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 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.
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.
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
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|Recent citations in the news|
Timescale Announces OpenTelemetry Tracing Support for Promscale
Timescale launches the new Timescale Cloud, a hosted relational database for time-series
Understanding Hyperfunctions in TimescaleDB
Timescale Valuation Rockets to Over $1B with $110M Round, Marking the Explosive Rise of Time-Series Data
How time series platforms unlock the potential of IoT: Join theCUBE for May 17 event
provided by Google News
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