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

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

Editorial information provided by DB-Engines
NameMarkLogic  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonOrigoDB  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 databaseA Wide Column Store for rapid development using massive semi-structured datasetsA fully ACID in-memory object graph databaseSpark 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
Wide column storeDocument store
Object oriented DBMS
Relational 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
Score4.04
Rank#77  Overall
#6  Wide column stores
Score0.06
Rank#380  Overall
#50  Document stores
#18  Object oriented DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.progress.com/­marklogicazure.microsoft.com/­en-us/­services/­storage/­tablesorigodb.comspark.apache.org/­sql
Technical documentationwww.progress.com/­marklogic/­documentationorigodb.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperMarkLogic Corp.MicrosoftRobert Friberg et alApache Software FoundationTeradata
Initial release200120122009 infounder the name LiveDB20142005
Current release11.0, December 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial inforestricted free version is availablecommercialOpen SourceOpen Source infoApache 2.0commercial
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++C#Scala
Server operating systemsLinux
OS X
Windows
hostedLinux
Windows
Linux
OS X
Windows
Linux
Data schemeschema-free infoSchema can be enforcedschema-freeyesyesFlexible 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 dateyesyesUser defined using .NET types and collectionsyesyes
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.yesnono infocan be achieved using .NETnoyes infoin Aster File Store
Secondary indexesyesnoyesnoyes
SQL infoSupport of SQLyes infoSQL92nonoSQL-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
RESTful HTTP API.NET Client API
HTTP API
LINQ
JDBC
ODBC
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.NetJava
Python
R
Scala
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresyes infovia XQuery or JavaScriptnoyesnoR packages
Triggersyesnoyes infoDomain Eventsnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicehorizontal partitioning infoclient side managed; servers are not synchronizedyes, 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.Source-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 jobsnonoyes 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 integritynonodepending on modelnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infocan act as a resource manager in an XA/JTA transactionoptimistic lockingACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoWrite ahead logyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes, with Range Indexesnoyesnono
User concepts infoAccess controlRole-based access control at the document and subdocument levelsAccess rights based on private key authentication or shared access signaturesRole based authorizationnofine grained access rights according to SQL-standard

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More resources
MarkLogicMicrosoft Azure Table StorageOrigoDBSpark SQLTeradata Aster
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