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

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

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Editorial information provided by DB-Engines
NameKdb  Xexclude from comparisonMarkLogic  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.
DescriptionHigh performance Time Series DBMSOperational 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 types
Primary database modelTime Series DBMS
Vector DBMS
Document store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMSRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.55
Rank#53  Overall
#3  Time Series DBMS
#1  Vector DBMS
Score5.92
Rank#58  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#6  Search engines
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitekx.comwww.marklogic.comspark.apache.org/­sql
Technical documentationcode.kx.comdocs.marklogic.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperKx Systems, a division of First Derivatives plcMarkLogic Corp.Apache Software FoundationTeradata
Initial release2000 infokdb was released 2000, kdb+ in 2003200120142005
Current release3.6, May 201811.0, December 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infofree 32-bit versioncommercial inforestricted free version is availableOpen 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 languageqC++Scala
Server operating systemsLinux
OS X
Solaris
Windows
Linux
OS X
Windows
Linux
OS X
Windows
Linux
Data schemeyesschema-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 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.yesyesnoyes infoin Aster File Store
Secondary indexesyes infotable attribute 'grouped'yesnoyes
SQL infoSupport of SQLSQL-like query language (q)yes infoSQL92SQL-like DML and DDL statementsyes
APIs and other access methodsHTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
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
JDBC
ODBC
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java
Python
R
Scala
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresuser defined functionsyes infovia XQuery or JavaScriptnoR packages
Triggersyes infowith viewsyesnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesnoneyes 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 methodsno infosimilar paradigm used for internal processingyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsyes 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 integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infocan act as a resource manager in an XA/JTA transactionnoACID
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.yesyes, with Range Indexesnono
User concepts infoAccess controlrights management via user accountsRole-based access control at the document and subdocument levelsnofine grained access rights according to SQL-standard
More information provided by the system vendor
KdbMarkLogicSpark SQLTeradata Aster
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
» more

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KdbMarkLogicSpark SQLTeradata Aster
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