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DBMS > TDengine

TDengine Systemeigenschaften

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

Unsere Besucher vergleichen TDengine oft mit InfluxDB, TimescaleDB und ClickHouse.

Redaktionelle Informationen bereitgestellt von DB-Engines
NameTDengine
KurzbeschreibungTime Series DBMS and big data platform
Primäres DatenbankmodellTime Series DBMS
Sekundäre DatenbankmodelleRelational DBMS
DB-Engines Ranking infomisst die Popularität von Datenbankmanagement- systemenranking trend
Trend Chart
Punkte0,49
Rang#239  Overall
#18  Time Series DBMS
Websitegithub.com/­taosdata/­TDengine
www.taosdata.com
Technische Dokumentationwww.taosdata.com/­en/­documentation
EntwicklerTaos Data
Erscheinungsjahr2019
Lizenz infoCommercial or Open SourceOpen Source infoGPL V3, also commercial editions available
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.
ImplementierungsspracheC
Server BetriebssystemeLinux
Datenschemaja
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, XSLTnein
Sekundärindizesnein
SQL infoSupport of SQLSQL-like query language
APIs und andere ZugriffskonzepteJDBC
RESTful HTTP API
Unterstützte Programmiersprachen.Net
C
C++
Go
Java
JavaScript (Node.js)
Lua
Python
Rust
Server-seitige Scripts infoStored Proceduresnein
Triggersyes, via alarm monitoring
Partitionierungsmechanismen infoMethoden zum Speichern von unterschiedlichen Daten auf unterschiedlichen KnotenSharding
Replikationsmechanismen infoMethoden zum redundanten Speichern von Daten auf mehreren Knotenja
Fremdschlüssel inforeferenzielle Integritätnein
Concurrency infoUnterstützung von gleichzeitig ausgeführten Datenmanipulationenja
Durability infoDauerhafte Speicherung der Datenja
Berechtigungskonzept infoZugriffskontrolleyes
Weitere Informationen bereitgestellt vom Systemhersteller
TDengine
Specific characteristics

One of the modules of TDengine is the time-series database. However, in addition to this, to reduce the complexity of research and development and the difficulty of system operation, TDengine also provides functions such as caching, message queuing, subscription, stream computing, etc. TDengine provides a full-stack technical solution for the processing of IoT and Industrial Internet BigData. It is an efficient and easy-to-use IoT Big Data platform.

TDengine uses standard SQL language to provide main functions and follow standardization specifications.

Clustered feature is open-sourced.

Competitive advantages
  • Performance improvement over 10 times: An innovative data storage structure is defined, with each single core can process at least 20,000 requests per second, insert millions of data points, and read more than 10 million data points, which is more than 10 times faster than other existing general database.
  • Reduce the cost of hardware or cloud services to 1/5: Due to its ultra-performance, TDengine’s computing resources consumption is less than 1/5 of other common Big Data solutions; through columnar storage and advanced compression algorithms, the storage consumption is less than 1/10 of other general databases.
  • Full-stack time-series data processing engine: Integrate database, message queue, cache, stream computing, and other functions, and the applications do not need to integrate with software such as Kafka/Redis/HBase/Spark/HDFS, thus greatly reducing the complexity cost of application development and maintenance.
  • Powerful analysis functions: Data from ten years ago or one second ago, can all be queried based on a specified time range. Data can be aggregated on a timeline or multiple devices. Ad-hoc queries can be made at any time through Shell, Python, R, and MATLAB.
  • Seamless connection with third-party tools: Integration with Telegraf, Grafana, EMQ, HiveMQ, Prometheus, MATLAB, R, etc. without even one single line of code. OPC, Hadoop, Spark, etc. will be supported in the future, and more BI tools will be seamlessly connected to.
  • Zero operation cost & zero learning cost: Installing clusters is simple and quick, with real-time backup built-in, and no need to split libraries or tables. Similar to standard SQL, TDengine can support RESTful, Python/Java/C/C + +/C#/Go/Node.js, and similar to MySQL with zero learning cost.
Typical application scenarios
  •  IT Infrastructure, Servers and Applications Monitoring
  •  Internet of Cars, Trucks, Ships, Bikes, Train, Airplanes
  •  Power Grids, Power Plants, Power Distribution, and Smart Meters
  •  Robotics, Elevators, Excavators, and other Machinery
  •  Oil/Gas Extraction, Oil Refineries, Oil Pipelines
  •  Water, Air and Other Forms of Environmental Monitoring
  •  Smart Homes, Buildings, Parks, and Cities
  •  Records of Internet Access, Phone Usage, and Financial Transactions
  •  Any Internet of Things and Industrial Internet Scenarios
Market metrics

Fastest growing database

With more than 15,500 stars on GitHub

Licensing and pricing models

Open Source (AGPL v3)

Enterprise / Cloud (https://www.taosdata.com/en/support/)

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Weitere Ressourcen
TDengine
Erwähnungen in aktuellen Nachrichten

"Open Source, Contribution, and Inspiration" -- The 2nd Anniversary of TDengine Open Source Community
14. Juli 2021, PRNewswire

TAOS Data Completes $47 Million Series B Financing led by MatrixPartners China, followed by Sequoia Capital China, GGV Capital, and Index Capital
24. Mai 2021, PRNewswire

bereitgestellt von Google News



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