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DBMS > MarkLogic vs. Quasardb vs. Spark SQL vs. Teradata

System Properties Comparison MarkLogic vs. Quasardb vs. Spark SQL vs. Teradata

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Editorial information provided by DB-Engines
NameMarkLogic  Xexclude from comparisonQuasardb  Xexclude from comparisonSpark SQL  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionOperational and transactional Enterprise NoSQL databaseDistributed, high-performance timeseries databaseSpark SQL is a component on top of 'Spark Core' for structured data processingA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Time Series DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.92
Rank#58  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#6  Search engines
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score45.33
Rank#21  Overall
#15  Relational DBMS
Websitewww.marklogic.comquasar.aispark.apache.org/­sqlwww.teradata.com
Technical documentationdocs.marklogic.comdoc.quasar.ai/­masterspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.teradata.com
DeveloperMarkLogic Corp.quasardbApache Software FoundationTeradata
Initial release2001200920141984
Current release11.0, December 20223.14.1, January 20243.5.0 ( 2.13), September 2023Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open Sourcecommercial inforestricted free version is availablecommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen 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++Scala
Server operating systemsLinux
OS X
Windows
BSD
Linux
OS X
Windows
Linux
OS X
Windows
hosted
Linux
Data schemeschema-free infoSchema can be enforcedschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes infointeger and binaryyesyes
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
Secondary indexesyesyes infowith tagsnoyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLyes infoSQL92SQL-like query languageSQL-like DML and DDL statementsyes infoSQL 2016 + extensions
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
HTTP APIJDBC
ODBC
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesC
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Java
Python
R
Scala
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresyes infovia XQuery or JavaScriptnonoyes infoUDFs, stored procedures, table functions in parallel
Triggersyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoconsistent hashingyes, utilizing Spark CoreSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replication with selectable replication factornoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobswith Hadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate 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 transactionACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoby using LevelDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes, with Range Indexesyes infoTransient modenoyes
User concepts infoAccess controlRole-based access control at the document and subdocument levelsCryptographically strong user authentication and audit trailnofine grained access rights according to SQL-standard

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More resources
MarkLogicQuasardbSpark SQLTeradata
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