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DBMS > Apache IoTDB vs. EXASOL vs. HBase vs. MarkLogic

System Properties Comparison Apache IoTDB vs. EXASOL vs. HBase vs. MarkLogic

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonEXASOL  Xexclude from comparisonHBase  Xexclude from comparisonMarkLogic  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.Wide-column store based on Apache Hadoop and on concepts of BigTableOperational and transactional Enterprise NoSQL database
Primary database modelTime Series DBMSRelational DBMSWide column storeDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
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
Score30.50
Rank#26  Overall
#2  Wide column stores
Score5.92
Rank#58  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#6  Search engines
Websiteiotdb.apache.orgwww.exasol.comhbase.apache.orgwww.marklogic.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.exasol.com/­resourceshbase.apache.org/­book.htmldocs.marklogic.com
DeveloperApache Software FoundationExasolApache Software Foundation infoApache top-level project, originally developed by PowersetMarkLogic Corp.
Initial release2018200020082001
Current release1.1.0, April 20232.3.4, January 202111.0, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache version 2commercial inforestricted free version is available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
Unix
Windows infousing Cygwin
Linux
OS X
Windows
Data schemeyesyesschema-free, schema definition possibleschema-free infoSchema can be enforced
Typing infopredefined data types such as float or dateyesyesoptions to bring your own types, AVROyes
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 indexesyesyesnoyes
SQL infoSupport of SQLSQL-like query languageyesnoyes infoSQL92
APIs and other access methodsJDBC
Native API
.Net
JDBC
ODBC
WebSocket
Java API
RESTful HTTP API
Thrift
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
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Java
Lua
Python
R
C
C#
C++
Groovy
Java
PHP
Python
Scala
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresyesuser defined functionsyes infoCoprocessors in Javayes infovia XQuery or JavaScript
Triggersyesyesyesyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingSharding
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 replication
Source-replica replication
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyes infoHadoop integrationyesyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDSingle row ACID (across millions of columns)ACID infocan act as a resource manager in an XA/JTA transaction
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesyes, with Range Indexes
User concepts infoAccess controlyesAccess rights for users, groups and roles according to SQL-standardAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACRole-based access control at the document and subdocument levels

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Apache IoTDBEXASOLHBaseMarkLogic
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