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DBMS > MarkLogic vs. Oracle Berkeley DB vs. Spark SQL vs. TimesTen

System Properties Comparison MarkLogic vs. Oracle Berkeley DB vs. Spark SQL vs. TimesTen

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Editorial information provided by DB-Engines
NameMarkLogic  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTimesTen  Xexclude from comparison
DescriptionOperational and transactional Enterprise NoSQL databaseWidely used in-process key-value storeSpark SQL is a component on top of 'Spark Core' for structured data processingIn-Memory RDBMS compatible to Oracle
Primary database modelDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Key-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.92
Rank#58  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#6  Search engines
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score1.31
Rank#163  Overall
#74  Relational DBMS
Websitewww.marklogic.comwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlspark.apache.org/­sqlwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationdocs.marklogic.comdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.oracle.com/­database/­timesten-18.1
DeveloperMarkLogic Corp.Oracle infooriginally developed by Sleepycat, which was acquired by OracleApache Software FoundationOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release2001199420141998
Current release11.0, December 202218.1.40, May 20203.5.0 ( 2.13), September 202311 Release 2 (11.2.2.8.0)
License infoCommercial or Open Sourcecommercial inforestricted free version is availableOpen Source infocommercial license availableOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C, Java, C++ (depending on the Berkeley DB edition)Scala
Server operating systemsLinux
OS X
Windows
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Windows
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeschema-free infoSchema can be enforcedschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyes
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.yesyes infoonly with the Berkeley DB XML editionnono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLyes infoSQL92yes infoSQL interfaced based on SQLite is availableSQL-like DML and DDL statementsyes
APIs and other access methodsJava API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
JDBC
ODBC
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languagesC
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
Java
Python
R
Scala
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresyes infovia XQuery or JavaScriptnonoPL/SQL
Triggersyesyes infoonly for the SQL APInono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infocan act as a resource manager in an XA/JTA transactionACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes, with Range Indexesyesnoyes
User concepts infoAccess controlRole-based access control at the document and subdocument levelsnonofine grained access rights according to SQL-standard

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More resources
MarkLogicOracle Berkeley DBSpark SQLTimesTen
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