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DBMS > MarkLogic vs. RDF4J vs. Solr vs. Teradata Aster

System Properties Comparison MarkLogic vs. RDF4J vs. Solr vs. Teradata Aster

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Editorial information provided by DB-Engines
NameMarkLogic  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSolr  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.
DescriptionOperational and transactional Enterprise NoSQL databaseRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.A widely used distributed, scalable search engine based on Apache LucenePlatform for big data analytics on multistructured data sources and types
Primary database modelDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
RDF storeSearch engineRelational DBMS
Secondary database modelsSpatial DBMS
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
Score0.74
Rank#222  Overall
#9  RDF stores
Score41.02
Rank#24  Overall
#3  Search engines
Websitewww.progress.com/­marklogicrdf4j.orgsolr.apache.org
Technical documentationwww.progress.com/­marklogic/­documentationrdf4j.org/­documentationsolr.apache.org/­resources.html
DeveloperMarkLogic Corp.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.Apache Software FoundationTeradata
Initial release2001200420062005
Current release11.0, December 20229.6.1, May 2024
License infoCommercial or Open Sourcecommercial inforestricted free version is availableOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaJava
Server operating systemsLinux
OS X
Windows
Linux
OS X
Unix
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
Data schemeschema-free infoSchema can be enforcedyes infoRDF Schemasyes infoDynamic Fields enables on-the-fly addition of new fieldsFlexible 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 dateyesyesyes infosupports customizable data types and automatic typingyes
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.yesyesyes infoin Aster File Store
Secondary indexesyesyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLyes infoSQL92noSolr Parallel SQL Interfaceyes
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
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Java API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java
PHP
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresyes infovia XQuery or JavaScriptyesJava pluginsR packages
Triggersyesyesyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneyesyes 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 methodsyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infocan act as a resource manager in an XA/JTA transactionACID infoIsolation support depends on the API usedoptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoin-memory storage is supported as wellyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes, with Range Indexesyesno
User concepts infoAccess controlRole-based access control at the document and subdocument levelsnoyesfine grained access rights according to SQL-standard

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More resources
MarkLogicRDF4J infoformerly known as SesameSolrTeradata Aster
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