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DBMS > Apache IoTDB vs. Heroic vs. Linter vs. MarkLogic vs. UniData,UniVerse

System Properties Comparison Apache IoTDB vs. Heroic vs. Linter vs. MarkLogic vs. UniData,UniVerse

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonHeroic  Xexclude from comparisonLinter  Xexclude from comparisonMarkLogic  Xexclude from comparisonUniData,UniVerse  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 FlinkTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchRDBMS for high security requirementsOperational and transactional Enterprise NoSQL databaseMultiValue database and application server with SQL mapping layer and meta database capabilities
Primary database modelTime Series DBMSTime Series DBMSRelational DBMSDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Multivalue DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score0.12
Rank#350  Overall
#152  Relational DBMS
Score5.18
Rank#63  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#7  Search engines
Score2.85
Rank#98  Overall
#1  Multivalue DBMS
Websiteiotdb.apache.orggithub.com/­spotify/­heroiclinter.ruwww.progress.com/­marklogicwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-unidata
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlspotify.github.io/­heroicwww.progress.com/­marklogic/­documentationdocs.rocketsoftware.com/­bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata
DeveloperApache Software FoundationSpotifyrelex.ruMarkLogic Corp.Rocket Software
Initial release20182014199020011985
Current release1.1.0, April 202311.0, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0commercialcommercial inforestricted free version is availablecommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC and C++C++C
Server operating systemsAll OS with a Java VM (>= 1.8)AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Linux
OS X
Windows
AIX
HP-UX
Linux
Solaris
Windows
Data schemeyesschema-freeyesschema-free infoSchema can be enforcedschema-free
Typing infopredefined data types such as float or dateyesyesyesyesoptional
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 indexesyesyes infovia Elasticsearchyesyesyes
SQL infoSupport of SQLSQL-like query languagenoyesyes infoSQL92yes
APIs and other access methodsJDBC
Native API
HQL (Heroic Query Language, a JSON-based language)
HTTP API
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
Java API infoJPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Basic infoU2 Basic
C
Java
Server-side scripts infoStored proceduresyesnoyes infoproprietary syntax with the possibility to convert from PL/SQLyes infovia XQuery or JavaScriptyes
Triggersyesnoyesyesyes infoU2 Basic
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingnoneShardingnone
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 replicationyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonoyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID infocan act as a resource manager in an XA/JTA transactionACID infoconfigurable
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.yesnoyes, with Range Indexes
User concepts infoAccess controlyesfine grained access rights according to SQL-standardRole-based access control at the document and subdocument levelsAccess rights according to SQL-standard and operating system based

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More resources
Apache IoTDBHeroicLinterMarkLogicUniData,UniVerse
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