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DBMS > Apache IoTDB vs. jBASE vs. MarkLogic vs. Sphinx vs. Tkrzw

System Properties Comparison Apache IoTDB vs. jBASE vs. MarkLogic vs. Sphinx vs. Tkrzw

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonjBASE  Xexclude from comparisonMarkLogic  Xexclude from comparisonSphinx  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  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 FlinkA robust multi-value DBMS comprising development tools and middlewareOperational and transactional Enterprise NoSQL databaseOpen source search engine for searching in data from different sources, e.g. relational databasesA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelTime Series DBMSMultivalue DBMSDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Search engineKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score1.49
Rank#156  Overall
#3  Multivalue DBMS
Score5.18
Rank#63  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#7  Search engines
Score5.95
Rank#55  Overall
#5  Search engines
Score0.07
Rank#372  Overall
#57  Key-value stores
Websiteiotdb.apache.orgwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-jbasewww.progress.com/­marklogicsphinxsearch.comdbmx.net/­tkrzw
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.rocketsoftware.com/­bundle?labelkey=jbase_5.9www.progress.com/­marklogic/­documentationsphinxsearch.com/­docs
DeveloperApache Software FoundationRocket Software (formerly Zumasys)MarkLogic Corp.Sphinx Technologies Inc.Mikio Hirabayashi
Initial release20181991200120012020
Current release1.1.0, April 20235.711.0, December 20223.5.1, February 20230.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial inforestricted free version is availableOpen Source infoGPL version 2, commercial licence availableOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C++C++
Server operating systemsAll OS with a Java VM (>= 1.8)AIX
Linux
Windows
Linux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
macOS
Data schemeyesschema-freeschema-free infoSchema can be enforcedyesschema-free
Typing infopredefined data types such as float or dateyesoptionalyesnono
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.noyesyesno
Secondary indexesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query languageEmbedded SQL for jBASE in BASICyes infoSQL92SQL-like query language (SphinxQL)no
APIs and other access methodsJDBC
Native API
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API
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
Proprietary protocol
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
Basic
Jabbascript
Java
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresyesyesyes infovia XQuery or JavaScriptnono
Triggersyesyesyesnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supportednone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesyesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infocan act as a resource manager in an XA/JTA transactionno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes, with Range Indexesyes infousing specific database classes
User concepts infoAccess controlyesAccess rights can be defined down to the item levelRole-based access control at the document and subdocument levelsnono

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Apache IoTDBjBASEMarkLogicSphinxTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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