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

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

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Editorial information provided by DB-Engines
NameMarkLogic  Xexclude from comparisonopenGauss  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 databaseAn enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by HuaweiSpark 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
Relational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial 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
Score1.05
Rank#189  Overall
#87  Relational DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websitewww.marklogic.comgitee.com/­opengauss
opengauss.org
spark.apache.org/­sql
Technical documentationdocs.marklogic.comdocs.opengauss.org/­en
gitee.com/­opengauss/­docs
spark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperMarkLogic Corp.Huawei and openGauss communityApache Software FoundationTeradata
Initial release2001201920142005
Current release11.0, December 20223.0, March 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial inforestricted free version is availableOpen SourceOpen 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, C++, JavaScala
Server operating systemsLinux
OS X
Windows
LinuxLinux
OS X
Windows
Linux
Data schemeschema-free infoSchema can be enforcedyesyesFlexible 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 infoSQL92ANSI SQL 2011SQL-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
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C++
Java
Java
Python
R
Scala
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresyes infovia XQuery or JavaScriptyesnoR packages
Triggersyesyesnono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by range, list and hash)yes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica 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 jobsnoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesnono
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 Indexesnonono
User concepts infoAccess controlRole-based access control at the document and subdocument levelsAccess rights for users, groups and roles according to SQL-standardnofine grained access rights according to SQL-standard

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More resources
MarkLogicopenGaussSpark SQLTeradata Aster
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