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DBMS > MarkLogic vs. Pinecone vs. Spark SQL vs. Teradata Aster vs. Trafodion

System Properties Comparison MarkLogic vs. Pinecone vs. Spark SQL vs. Teradata Aster vs. Trafodion

Editorial information provided by DB-Engines
NameMarkLogic  Xexclude from comparisonPinecone  Xexclude from comparisonSpark SQL  Xexclude from comparisonTeradata Aster  Xexclude from comparisonTrafodion  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionOperational and transactional Enterprise NoSQL databaseA managed, cloud-native vector databaseSpark SQL is a component on top of 'Spark Core' for structured data processingPlatform for big data analytics on multistructured data sources and typesTransactional SQL-on-Hadoop DBMS
Primary database modelDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Vector DBMSRelational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.18
Rank#63  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#7  Search engines
Score3.23
Rank#92  Overall
#2  Vector DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.marklogic.comwww.pinecone.iospark.apache.org/­sqltrafodion.apache.org
Technical documentationdocs.marklogic.comdocs.pinecone.io/­docs/­overviewspark.apache.org/­docs/­latest/­sql-programming-guide.htmltrafodion.apache.org/­documentation.html
DeveloperMarkLogic Corp.Pinecone Systems, IncApache Software FoundationTeradataApache Software Foundation, originally developed by HP
Initial release20012019201420052014
Current release11.0, December 20223.5.0 ( 2.13), September 20232.3.0, February 2019
License infoCommercial or Open Sourcecommercial inforestricted free version is availablecommercialOpen Source infoApache 2.0commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++ScalaC++, Java
Server operating systemsLinux
OS X
Windows
hostedLinux
OS X
Windows
LinuxLinux
Data schemeschema-free infoSchema can be enforcedyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Storeyes
Typing infopredefined data types such as float or dateyesString, Number, Booleanyesyesyes
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 Storeno
Secondary indexesyesnoyesyes
SQL infoSupport of SQLyes infoSQL92noSQL-like DML and DDL statementsyesyes
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
RESTful HTTP APIJDBC
ODBC
ADO.NET
JDBC
ODBC
OLE DB
ADO.NET
JDBC
ODBC
Supported programming languagesC
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
PythonJava
Python
R
Scala
C
C#
C++
Java
Python
R
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresyes infovia XQuery or JavaScriptnoR packagesJava Stored Procedures
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark CoreShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.yes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsnoyes infoSQL Map-Reduce Frameworkyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
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 transactionnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes, with Range Indexesnononono
User concepts infoAccess controlRole-based access control at the document and subdocument levelsnofine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
MarkLogicPineconeSpark SQLTeradata AsterTrafodion
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