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DBMS > Apache IoTDB vs. Atos Standard Common Repository vs. Netezza vs. Postgres-XL vs. SpatiaLite

System Properties Comparison Apache IoTDB vs. Atos Standard Common Repository vs. Netezza vs. Postgres-XL vs. SpatiaLite

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonPostgres-XL  Xexclude from comparisonSpatiaLite  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
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 FlinkHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksData warehouse and analytics appliance part of IBM PureSystemsBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresSpatial extension of SQLite
Primary database modelTime Series DBMSDocument store
Key-value store
Relational DBMSRelational DBMSSpatial DBMS
Secondary database modelsDocument store
Spatial DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.19
Rank#176  Overall
#15  Time Series DBMS
Score10.18
Rank#46  Overall
#29  Relational DBMS
Score0.52
Rank#256  Overall
#117  Relational DBMS
Score1.72
Rank#149  Overall
#3  Spatial DBMS
Websiteiotdb.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.ibm.com/­products/­netezzawww.postgres-xl.orgwww.gaia-gis.it/­fossil/­libspatialite/­index
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.postgres-xl.org/­documentationwww.gaia-gis.it/­gaia-sins/­spatialite_topics.html
DeveloperApache Software FoundationAtos Convergence CreatorsIBMAlessandro Furieri
Initial release2018201620002014 infosince 2012, originally named StormDB2008
Current release1.1.0, April 2023170310 R1, October 20185.0.0, August 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoMozilla public licenseOpen Source infoMPL 1.1, GPL v2.0 or LGPL v2.1
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaCC++
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxLinux infoincluded in applianceLinux
macOS
server-less
Data schemeyesSchema and schema-less with LDAP viewsyesyesyes
Typing infopredefined data types such as float or dateyesoptionalyesyesyes
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.noyesyes infoXML type, but no XML query functionalityno
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like query languagenoyesyes infodistributed, parallel query executionyes
APIs and other access methodsJDBC
Native API
LDAPJDBC
ODBC
OLE DB
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
All languages with LDAP bindingsC
C++
Fortran
Java
Lua
Perl
Python
R
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresyesnoyesuser defined functionsno
Triggersyesyesnoyesyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infocell divisionShardinghorizontal partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsACIDACID infoMVCCACID
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.yesyesnoyes
User concepts infoAccess controlyesLDAP bind authenticationUsers with fine-grained authorization conceptfine grained access rights according to SQL-standardno

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More resources
Apache IoTDBAtos Standard Common RepositoryNetezza infoAlso called PureData System for Analytics by IBMPostgres-XLSpatiaLite
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