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

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

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Editorial information provided by DB-Engines
NameMarkLogic  Xexclude from comparisonSpark SQL  Xexclude from comparisonTeradata Aster  Xexclude from comparisonVoltDB  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 typesDistributed In-Memory NewSQL RDBMS infoUsed for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory
Primary database modelDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score6.50
Rank#56  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#5  Search engines
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score1.46
Rank#159  Overall
#74  Relational DBMS
Websitewww.marklogic.comspark.apache.org/­sqlwww.voltdb.com
Technical documentationdocs.marklogic.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.voltdb.com
DeveloperMarkLogic Corp.Apache Software FoundationTeradataVoltDB Inc.
Initial release2001201420052010
Current release11.0, December 20223.5.0 ( 2.13), September 202311.3, April 2022
License infoCommercial or Open Sourcecommercial inforestricted free version is availableOpen Source infoApache 2.0commercialOpen Source infoAGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions
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++ScalaJava, C++
Server operating systemsLinux
OS X
Windows
Linux
OS X
Windows
LinuxLinux
OS X infofor development
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 Storeyes
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 statementsyesyes infoonly a subset of SQL 99
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
Java API
JDBC
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java
Python
R
Scala
C
C#
C++
Java
Python
R
C#
C++
Erlang infonot officially supported
Go
Java
JavaScript infoNode.js
PHP
Python
Server-side scripts infoStored proceduresyes infovia XQuery or JavaScriptnoR packagesJava
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark CoreShardingSharding
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
Source-replica replication
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 infoFOREIGN KEY constraints are not supported
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infocan act as a resource manager in an XA/JTA transactionnoACIDACID infoTransactions are executed single-threaded within stored procedures
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoData access is serialized by the server
Durability infoSupport for making data persistentyesyesyesyes infoSnapshots and command logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes, with Range Indexesnono
User concepts infoAccess controlRole-based access control at the document and subdocument levelsnofine grained access rights according to SQL-standardUsers and roles with access to stored procedures

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More resources
MarkLogicSpark SQLTeradata AsterVoltDB
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