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DBMS > Apache IoTDB vs. IBM Cloudant vs. MarkLogic vs. TimescaleDB

System Properties Comparison Apache IoTDB vs. IBM Cloudant vs. MarkLogic vs. TimescaleDB

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonIBM Cloudant  Xexclude from comparisonMarkLogic  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 FlinkDatabase as a Service offering based on Apache CouchDBOperational and transactional Enterprise NoSQL databaseA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelTime Series DBMSDocument storeDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Time 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
Score2.68
Rank#106  Overall
#20  Document stores
Score5.92
Rank#58  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#6  Search engines
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websiteiotdb.apache.orgwww.ibm.com/­products/­cloudantwww.marklogic.comwww.timescale.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlcloud.ibm.com/­docs/­Cloudantdocs.marklogic.comdocs.timescale.com
DeveloperApache Software FoundationIBM, Apache Software Foundation infoIBM acquired Cloudant in February 2014MarkLogic Corp.Timescale
Initial release2018201020012017
Current release1.1.0, April 202311.0, December 20222.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial inforestricted free version is availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaErlangC++C
Server operating systemsAll OS with a Java VM (>= 1.8)hostedLinux
OS X
Windows
Linux
OS X
Windows
Data schemeyesschema-freeschema-free infoSchema can be enforcedyes
Typing infopredefined data types such as float or dateyesnoyesnumerics, 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.nonoyesyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query languagenoyes infoSQL92yes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
Native API
RESTful HTTP/JSON APIJava API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#
Java
JavaScript
Objective-C
PHP
Ruby
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyesView functions (Map-Reduce) in JavaScriptyes infovia XQuery or JavaScriptuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyesyesyesyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingyes, 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 replicasMulti-source replication
Source-replica replication
yesSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesyes 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 ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infoatomic operations within a document possibleACID infocan act as a resource manager in an XA/JTA transactionACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoOptimistic lockingyesyes
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.yesnoyes, with Range Indexesno
User concepts infoAccess controlyesAccess rights for users can be defined per databaseRole-based access control at the document and subdocument levelsfine grained access rights according to SQL-standard

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More resources
Apache IoTDBIBM CloudantMarkLogicTimescaleDB
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