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DBMS > gStore vs. MarkLogic vs. Microsoft Azure Table Storage vs. Spark SQL vs. Teradata Aster

System Properties Comparison gStore vs. MarkLogic vs. Microsoft Azure Table Storage vs. Spark SQL vs. Teradata Aster

Editorial information provided by DB-Engines
NamegStore  Xexclude from comparisonMarkLogic  Xexclude from comparisonMicrosoft Azure Table Storage  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.
DescriptionA native Graph DBMS to store and maintain very large RDF datasets.Operational and transactional Enterprise NoSQL databaseA Wide Column Store for rapid development using massive semi-structured datasetsSpark 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 modelGraph DBMS
RDF store
Document store
Native XML DBMS
RDF store infoas of version 7
Search engine
Wide column storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#342  Overall
#34  Graph DBMS
#16  RDF stores
Score5.18
Rank#63  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#7  Search engines
Score4.04
Rank#77  Overall
#6  Wide column stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteen.gstore.cnwww.marklogic.comazure.microsoft.com/­en-us/­services/­storage/­tablesspark.apache.org/­sql
Technical documentationen.gstore.cn/­#/­enDocsdocs.marklogic.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperMarkLogic Corp.MicrosoftApache Software FoundationTeradata
Initial release20162001201220142005
Current release1.2, November 202311.0, December 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoBSDcommercial inforestricted free version is availablecommercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++Scala
Server operating systemsLinuxLinux
OS X
Windows
hostedLinux
OS X
Windows
Linux
Data schemeschema-free and OWL/RDFS-schema supportschema-free infoSchema can be enforcedschema-freeyesFlexible 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 dateyesyesyesyesyes
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.noyesnonoyes infoin Aster File Store
Secondary indexesyesnonoyes
SQL infoSupport of SQLnoyes infoSQL92noSQL-like DML and DDL statementsyes
APIs and other access methodsHTTP API
SPARQL 1.1
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
RESTful HTTP APIJDBC
ODBC
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC++
Java
JavaScript (Node.js)
PHP
Python
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresyesyes infovia XQuery or JavaScriptnonoR packages
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.noneyes 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 methodsnoyes 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 integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACID infocan act as a resource manager in an XA/JTA transactionoptimistic lockingnoACID
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.noyes, with Range Indexesnonono
User concepts infoAccess controlUsers, roles and permissions, Role-Based Access Control (RBAC) supportedRole-based access control at the document and subdocument levelsAccess rights based on private key authentication or shared access signaturesnofine grained access rights according to SQL-standard

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More resources
gStoreMarkLogicMicrosoft Azure Table StorageSpark SQLTeradata Aster
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