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DBMS > DataFS vs. MarkLogic vs. Spark SQL vs. Teradata Aster vs. WakandaDB

System Properties Comparison DataFS vs. MarkLogic vs. Spark SQL vs. Teradata Aster vs. WakandaDB

Editorial information provided by DB-Engines
NameDataFS  Xexclude from comparisonMarkLogic  Xexclude from comparisonSpark SQL  Xexclude from comparisonTeradata Aster  Xexclude from comparisonWakandaDB  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionAll data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.Operational 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 typesWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelObject oriented DBMSDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMSRelational DBMSObject oriented DBMS
Secondary database modelsGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.09
Rank#360  Overall
#17  Object oriented DBMS
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
Score0.10
Rank#356  Overall
#16  Object oriented DBMS
Websitenewdatabase.comwww.marklogic.comspark.apache.org/­sqlwakanda.github.io
Technical documentationdev.mobiland.com/­Overview.xspdocs.marklogic.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwakanda.github.io/­doc
DeveloperMobiland AGMarkLogic Corp.Apache Software FoundationTeradataWakanda SAS
Initial release20182001201420052012
Current release1.1.263, October 202211.0, December 20223.5.0 ( 2.13), September 20232.7.0 (April 29, 2019), April 2019
License infoCommercial or Open Sourcecommercialcommercial inforestricted free version is availableOpen Source infoApache 2.0commercialOpen Source infoAGPLv3, extended commercial license available
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++, JavaScript
Server operating systemsWindowsLinux
OS X
Windows
Linux
OS X
Windows
LinuxLinux
OS X
Windows
Data schemeClasses, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)schema-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 dateyesyesyesyesyes
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.noyesnoyes infoin Aster File Storeno
Secondary indexesnoyesnoyes
SQL infoSupport of SQLnoyes infoSQL92SQL-like DML and DDL statementsyesno
APIs and other access methods.NET Client API
Proprietary client DLL
WinRT client
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
RESTful HTTP API
Supported programming languages.Net
C
C#
C++
VB.Net
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java
Python
R
Scala
C
C#
C++
Java
Python
R
JavaScript
Server-side scripts infoStored proceduresyes infovia XQuery or JavaScriptnoR packagesyes
Triggersno, except callback-events from server when changes happenedyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesProprietary Sharding systemShardingyes, utilizing Spark CoreShardingnone
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.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes 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 ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infocan act as a resource manager in an XA/JTA transactionnoACIDACID
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.noyes, with Range Indexesnonono
User concepts infoAccess controlWindows-ProfileRole-based access control at the document and subdocument levelsnofine grained access rights according to SQL-standardyes

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More resources
DataFSMarkLogicSpark SQLTeradata AsterWakandaDB
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