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DBMS > MarkLogic vs. OrientDB vs. Spark SQL vs. Teradata Aster

System Properties Comparison MarkLogic vs. OrientDB vs. Spark SQL vs. Teradata Aster

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Editorial information provided by DB-Engines
NameMarkLogic  Xexclude from comparisonOrientDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionOperational and transactional Enterprise NoSQL databaseMulti-model DBMS (Document, Graph, Key/Value)Spark SQL is a component on top of 'Spark Core' for structured data processingPlatform for big data analytics on multistructured data sources and types
Primary database modelDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Document store
Graph DBMS
Key-value store
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score6.50
Rank#56  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#5  Search engines
Score3.27
Rank#97  Overall
#16  Document stores
#6  Graph DBMS
#15  Key-value stores
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websitewww.marklogic.comorientdb.orgspark.apache.org/­sql
Technical documentationdocs.marklogic.comwww.orientdb.com/­docs/­last/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperMarkLogic Corp.OrientDB LTD; CallidusCloud; SAPApache Software FoundationTeradata
Initial release2001201020142005
Current release11.0, December 20223.2.29, March 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial inforestricted free version is availableOpen Source infoApache version 2Open 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++JavaScala
Server operating systemsLinux
OS X
Windows
All OS with a Java JDK (>= JDK 6)Linux
OS X
Windows
Linux
Data schemeschema-free infoSchema can be enforcedschema-free infoSchema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")yesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesyesyesyes
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.yesnonoyes infoin Aster File Store
Secondary indexesyesyesnoyes
SQL infoSupport of SQLyes infoSQL92SQL-like query language, no joinsSQL-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
Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API
JDBC
ODBC
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala
Java
Python
R
Scala
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresyes infovia XQuery or JavaScriptJava, JavascriptnoR packages
TriggersyesHooksnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replicationnoneyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsno infocould be achieved with distributed queriesyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyes inforelationship in graphsnono
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 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.yes, with Range Indexesnono
User concepts infoAccess controlRole-based access control at the document and subdocument levelsAccess rights for users and roles; record level security configurablenofine grained access rights according to SQL-standard

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MarkLogicOrientDBSpark SQLTeradata Aster
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