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DBMS > TimescaleDB

TimescaleDB Systemeigenschaften

Bitte wählen Sie ein weiteres System aus, um es mit TimescaleDB zu vergleichen.

Unsere Besucher vergleichen TimescaleDB oft mit InfluxDB, PostgreSQL und Prometheus.

Redaktionelle Informationen bereitgestellt von DB-Engines
KurzbeschreibungA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primäres DatenbankmodellTime Series DBMS
Sekundäre DatenbankmodelleRelational DBMS
DB-Engines Ranking infomisst die Popularität von Datenbankmanagement- systemenranking trend
Trend Chart
Rang#100  Overall
#6  Time Series DBMS
Technische Dokumentationdocs.timescale.com
Lizenz infoCommercial or Open SourceOpen Source infoApache 2.0
Ausschließlich ein Cloud-Service infoNur als Cloud-Service verfügbarnein
DBaaS Angebote (gesponserte Links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Server BetriebssystemeLinux
Typisierung infovordefinierte Datentypen, z.B. float oder dateja
XML Unterstützung infoVerarbeitung von Daten in XML Format, beispielsweise Speicherung von XML-Strukturen und/oder Unterstützung von XPath, XQuery, XSLTja
SQL infoSupport of SQLja infofull PostgreSQL SQL syntax
APIs und andere ZugriffskonzepteADO.NET
native C library
streaming API for large objects
Unterstützte Programmiersprachen.Net
Java infoJDBC
Server-seitige Scripts infoStored Proceduresbenutzerdefinierte Funktionen, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Partitionierungsmechanismen infoMethoden zum Speichern von unterschiedlichen Daten auf unterschiedlichen Knotenyes, across time and space (hash partitioning) attributes
Replikationsmechanismen infoMethoden zum redundanten Speichern von Daten auf mehreren KnotenSource-Replica Replikation info
MapReduce infoBietet ein API für Map/Reduce Operationennein
Konsistenzkonzept infoMethoden zur Sicherstellung der Konsistenz in einem verteilten SystemImmediate Consistency
Fremdschlüssel inforeferenzielle Integritätja
Transaktionskonzept infoUnterstützung zur Sicherstellung der Datenintegrität bei nicht-atomaren DatenmanipulationenACID
Concurrency infoUnterstützung von gleichzeitig ausgeführten Datenmanipulationenja
Durability infoDauerhafte Speicherung der Datenja
In-Memory Unterstützung infoGibt es Möglichkeiten einige oder alle Strukturen nur im Hauptspeicher zu haltennein
Berechtigungskonzept infoZugriffskontrolleBenutzer mit feingranularem Berechtigungskonzept entsprechend SQL-Standard
Weitere Informationen bereitgestellt vom Systemhersteller
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).

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Weitere Ressourcen
Erwähnungen in aktuellen Nachrichten

QuestDB has built a lightning fast time series database. Can it build a business to match?
16. Februar 2021, TechRepublic

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

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

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

Timescale announces $15M investment and new enterprise version of TimescaleDB
29. Januar 2019, TechCrunch

bereitgestellt von Google News


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