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DBMS > Apache IoTDB vs. Cubrid vs. InfinityDB vs. Sphinx vs. TimescaleDB

System Properties Comparison Apache IoTDB vs. Cubrid vs. InfinityDB vs. Sphinx vs. TimescaleDB

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonCubrid  Xexclude from comparisonInfinityDB  Xexclude from comparisonSphinx  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkCUBRID is an open-source SQL-based relational database management system with object extensions for OLTPA Java embedded Key-Value Store which extends the Java Map interfaceOpen source search engine for searching in data from different sources, e.g. relational databasesA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelTime Series DBMSRelational DBMSKey-value storeSearch engineTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score1.20
Rank#169  Overall
#78  Relational DBMS
Score0.00
Rank#378  Overall
#57  Key-value stores
Score5.98
Rank#56  Overall
#5  Search engines
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websiteiotdb.apache.orgcubrid.com (korean)
cubrid.org (english)
boilerbay.comsphinxsearch.comwww.timescale.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlcubrid.org/­manualsboilerbay.com/­infinitydb/­manualsphinxsearch.com/­docsdocs.timescale.com
DeveloperApache Software FoundationCUBRID Corporation, CUBRID FoundationBoiler Bay Inc.Sphinx Technologies Inc.Timescale
Initial release20182008200220012017
Current release1.1.0, April 202311.0, January 20214.03.5.1, February 20232.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0commercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++, JavaJavaC++C
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
Windows
All OS with a Java VMFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeyesyesyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeyesyes
Typing infopredefined data types such as float or dateyesyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysnonumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.nononoyes
Secondary indexesyesyesno infomanual creation possible, using inversions based on multi-value capabilityyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL-like query languageyesnoSQL-like query language (SphinxQL)yes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
Native API
ADO.NET
JDBC
ODBC
OLE DB
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
Proprietary protocolADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
JavaC++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyesJava Stored Proceduresnonouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyesyesnonoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)nonenoneSharding infoPartitioning is done manually, search queries against distributed index is supportedyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasSource-replica replicationnonenoneSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate Consistency infoREAD-COMMITTED or SERIALIZEDImmediate Consistency
Foreign keys infoReferential integritynoyesno infomanual creation possible, using inversions based on multi-value capabilitynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoOptimistic locking for transactions; no isolation for bulk loadsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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.yesnonono
User concepts infoAccess controlyesfine grained access rights according to SQL-standardnonofine grained access rights according to SQL-standard

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Apache IoTDBCubridInfinityDBSphinxTimescaleDB
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