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DBMS > Apache Druid vs. Citus vs. HarperDB vs. TDengine

System Properties Comparison Apache Druid vs. Citus vs. HarperDB vs. TDengine

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonCitus  Xexclude from comparisonHarperDB  Xexclude from comparisonTDengine  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLUltra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.Time Series DBMS and big data platform
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSDocument storeTime Series DBMS
Secondary database modelsDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score2.15
Rank#117  Overall
#56  Relational DBMS
Score0.60
Rank#244  Overall
#38  Document stores
Score2.68
Rank#106  Overall
#9  Time Series DBMS
Websitedruid.apache.orgwww.citusdata.comwww.harperdb.iogithub.com/­taosdata/­TDengine
tdengine.com
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.citusdata.comdocs.harperdb.io/­docsdocs.tdengine.com
DeveloperApache Software Foundation and contributorsHarperDBTDEngine, previously Taos Data
Initial release2012201020172019
Current release29.0.1, April 20248.1, December 20183.1, August 20213.0, August 2022
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoAGPL, commercial license also availablecommercial infofree community edition availableOpen Source infoAGPL V3, also commercial editions available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCNode.jsC
Server operating systemsLinux
OS X
Unix
LinuxLinux
OS X
Linux
Windows
Data schemeyes infoschema-less columns are supportedyesdynamic schemayes
Typing infopredefined data types such as float or dateyesyesyes infoJSON data typesyes
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.noyes infospecific XML type available, but no XML query functionalitynono
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL for queryingyes infostandard, with numerous extensionsSQL-like data manipulation statementsStandard SQL with extensions for time-series applications
APIs and other access methodsJDBC
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
JDBC
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust
Server-side scripts infoStored proceduresnouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.Custom Functions infosince release 3.1no
Triggersnoyesnoyes, via alarm monitoring
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingA table resides as a whole on one (or more) nodes in a clusterSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesSource-replica replication infoother methods possible by using 3rd party extensionsyes infothe nodes on which a table resides can be definedyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
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 datanoACIDAtomic execution of specific operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes, using LMDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemfine grained access rights according to SQL-standardAccess rights for users and rolesyes
More information provided by the system vendor
Apache DruidCitusHarperDBTDengine
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 DruidCitusHarperDBTDengine
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