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DBMS > MarkLogic vs. Spark SQL vs. Teradata Aster vs. Transwarp StellarDB vs. Typesense

System Properties Comparison MarkLogic vs. Spark SQL vs. Teradata Aster vs. Transwarp StellarDB vs. Typesense

Editorial information provided by DB-Engines
NameMarkLogic  Xexclude from comparisonSpark SQL  Xexclude from comparisonTeradata Aster  Xexclude from comparisonTranswarp StellarDB  Xexclude from comparisonTypesense  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 databaseSpark SQL is a component on top of 'Spark Core' for structured data processingPlatform for big data analytics on multistructured data sources and typesA distributed graph DBMS built for enterprise-level graph applicationsA typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity
Primary database modelDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMSRelational DBMSGraph DBMSSearch engine
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
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.07
Rank#371  Overall
#39  Graph DBMS
Score0.76
Rank#219  Overall
#14  Search engines
Websitewww.marklogic.comspark.apache.org/­sqlwww.transwarp.cn/­en/­product/­stellardbtypesense.org
Technical documentationdocs.marklogic.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmltypesense.org/­docs
DeveloperMarkLogic Corp.Apache Software FoundationTeradataTranswarp
Initial release2001201420052015
Current release11.0, December 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial inforestricted free version is availableOpen Source infoApache 2.0commercialcommercialOpen Source infoGPL V3
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++ScalaC++
Server operating systemsLinux
OS X
Windows
Linux
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 Storeschema-free infopre-defined schema optional
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.yesnoyes infoin Aster File Store
Secondary indexesyesnoyesyes
SQL infoSupport of SQLyes infoSQL92SQL-like DML and DDL statementsyesSQL-like query languageno
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
ADO.NET
JDBC
ODBC
OLE DB
OpenCypherRESTful HTTP API
Supported programming languagesC
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java
Python
R
Scala
C
C#
C++
Java
Python
R
.Net infocommunity maintained
Clojure infocommunity maintained
Dart infocommunity maintained
Go infocommunity maintained
Java infocommunity maintained
JavaScript
Perl infocommunity maintained
PHP
Python
Ruby
Rust infocommunity maintained
Swift infocommunity maintained
Server-side scripts infoStored proceduresyes infovia XQuery or JavaScriptnoR packagesno
Triggersyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark CoreShardinghorizontal partitioning
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.Multi-source replication using RAFT
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsyes infoSQL Map-Reduce Frameworkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infocan act as a resource manager in an XA/JTA transactionnoACIDno
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 Indexesnonoyes
User concepts infoAccess controlRole-based access control at the document and subdocument levelsnofine grained access rights according to SQL-standardyes

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More resources
MarkLogicSpark SQLTeradata AsterTranswarp StellarDBTypesense
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