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DBMS > Apache Druid vs. Splice Machine vs. TDengine vs. Yanza

System Properties Comparison Apache Druid vs. Splice Machine vs. TDengine vs. Yanza

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonSplice Machine  Xexclude from comparisonTDengine  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkTime Series DBMS and big data platformTime Series DBMS for IoT Applications
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSTime Series DBMSTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score2.60
Rank#107  Overall
#8  Time Series DBMS
Websitedruid.apache.orgsplicemachine.comgithub.com/­taosdata/­TDengine
tdengine.com
yanza.com
Technical documentationdruid.apache.org/­docs/­latest/­designsplicemachine.com/­how-it-worksdocs.tdengine.com
DeveloperApache Software Foundation and contributorsSplice MachineTDEngine, previously Taos DataYanza
Initial release2012201420192015
Current release29.0.1, April 20243.1, March 20213.0, August 2022
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoAGPL 3.0, commercial license availableOpen Source infoAGPL V3, also commercial editions availablecommercial infofree version available
Cloud-based only infoOnly available as a cloud servicenononono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC
Server operating systemsLinux
OS X
Unix
Linux
OS X
Solaris
Windows
Linux
Windows
Windows
Data schemeyes infoschema-less columns are supportedyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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.nonono
Secondary indexesyesyesnono
SQL infoSupport of SQLSQL for queryingyesStandard SQL with extensions for time-series applicationsno
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
Native Spark Datasource
ODBC
JDBC
RESTful HTTP API
HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust
any language that supports HTTP calls
Server-side scripts infoStored proceduresnoyes infoJavanono
Triggersnoyesyes, via alarm monitoringyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShared Nothhing Auto-Sharding, Columnar PartitioningShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMulti-source replication
Source-replica replication
yesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users, groups and roles according to SQL-standardyesno
More information provided by the system vendor
Apache DruidSplice MachineTDengineYanza
Specific characteristicsTDengineā„¢ is a next generation data historian purpose-built for Industry 4.0 and...
» more
Competitive advantagesHigh Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» more
Typical application scenariosTDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» more
Market metricsTDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more
Licensing and pricing modelsTDengine OSS is an open source, cloud native time series database. It includes built-in...
» more
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More resources
Apache DruidSplice MachineTDengineYanza
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