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DBMS > Citus vs. Databricks vs. Sphinx vs. TDengine

System Properties Comparison Citus vs. Databricks vs. Sphinx vs. TDengine

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonDatabricks  Xexclude from comparisonSphinx  Xexclude from comparisonTDengine  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Open source search engine for searching in data from different sources, e.g. relational databasesTime Series DBMS and big data platform
Primary database modelRelational DBMSDocument store
Relational DBMS
Search engineTime Series DBMS
Secondary database modelsDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score2.60
Rank#107  Overall
#8  Time Series DBMS
Websitewww.citusdata.comwww.databricks.comsphinxsearch.comgithub.com/­taosdata/­TDengine
tdengine.com
Technical documentationdocs.citusdata.comdocs.databricks.comsphinxsearch.com/­docsdocs.tdengine.com
DeveloperDatabricksSphinx Technologies Inc.TDEngine, previously Taos Data
Initial release2010201320012019
Current release8.1, December 20183.5.1, February 20233.0, August 2022
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL V3, also commercial editions available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC++C
Server operating systemsLinuxhostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyesnoyes
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.yes infospecific XML type available, but no XML query functionalityyesno
Secondary indexesyesyesyes infofull-text index on all search fieldsno
SQL infoSupport of SQLyes infostandard, with numerous extensionswith Databricks SQLSQL-like query language (SphinxQL)Standard SQL with extensions for time-series applications
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
RESTful HTTP API
Proprietary protocolJDBC
RESTful HTTP API
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Python
R
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.user defined functions and aggregatesnono
Triggersyesnoyes, via alarm monitoring
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsyesnoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlfine grained access rights according to SQL-standardnoyes
More information provided by the system vendor
CitusDatabricksSphinxTDengine
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
TDengine™ 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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CitusDatabricksSphinxTDengine
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