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DBMS > Apache IoTDB vs. EXASOL vs. JaguarDB vs. Netezza vs. Postgres-XL

System Properties Comparison Apache IoTDB vs. EXASOL vs. JaguarDB vs. Netezza vs. Postgres-XL

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonEXASOL  Xexclude from comparisonJaguarDB  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonPostgres-XL  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 FlinkHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Performant, highly scalable DBMS for AI and IoT applicationsData warehouse and analytics appliance part of IBM PureSystemsBased on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelTime Series DBMSRelational DBMSKey-value store
Vector DBMS
Relational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score1.99
Rank#124  Overall
#58  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
#13  Vector DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score0.49
Rank#256  Overall
#117  Relational DBMS
Websiteiotdb.apache.orgwww.exasol.comwww.jaguardb.comwww.ibm.com/­products/­netezzawww.postgres-xl.org
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.exasol.com/­resourceswww.jaguardb.com/­support.htmlwww.postgres-xl.org/­documentation
DeveloperApache Software FoundationExasolDataJaguar, Inc.IBM
Initial release20182000201520002014 infosince 2012, originally named StormDB
Current release1.1.0, April 20233.3 July 202310 R1, October 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoGPL V3.0commercialOpen Source infoMozilla public license
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++ infothe server part. Clients available in other languagesC
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxLinux infoincluded in applianceLinux
macOS
Data schemeyesyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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 infoXML type, but no XML query functionality
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like query languageyesA subset of ANSI SQL is implemented infobut no views, foreign keys, triggersyesyes infodistributed, parallel query execution
APIs and other access methodsJDBC
Native API
.Net
JDBC
ODBC
WebSocket
JDBC
ODBC
JDBC
ODBC
OLE DB
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Java
Lua
Python
R
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
C
C++
Fortran
Java
Lua
Perl
Python
R
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresyesuser defined functionsnoyesuser defined functions
Triggersyesyesnonoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyes infoHadoop integrationnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACIDACID infoMVCC
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnono
User concepts infoAccess controlyesAccess rights for users, groups and roles according to SQL-standardrights management via user accountsUsers with fine-grained authorization conceptfine grained access rights according to SQL-standard

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More resources
Apache IoTDBEXASOLJaguarDBNetezza infoAlso called PureData System for Analytics by IBMPostgres-XL
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