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DBMS > Hazelcast vs. MarkLogic vs. Sphinx vs. Stardog

System Properties Comparison Hazelcast vs. MarkLogic vs. Sphinx vs. Stardog

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Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonMarkLogic  Xexclude from comparisonSphinx  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionA widely adopted in-memory data gridOperational and transactional Enterprise NoSQL databaseOpen source search engine for searching in data from different sources, e.g. relational databasesEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelKey-value storeDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Search engineGraph DBMS
RDF store
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.97
Rank#57  Overall
#6  Key-value stores
Score5.92
Rank#58  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#6  Search engines
Score5.98
Rank#56  Overall
#5  Search engines
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Websitehazelcast.comwww.marklogic.comsphinxsearch.comwww.stardog.com
Technical documentationhazelcast.org/­imdg/­docsdocs.marklogic.comsphinxsearch.com/­docsdocs.stardog.com
DeveloperHazelcastMarkLogic Corp.Sphinx Technologies Inc.Stardog-Union
Initial release2008200120012010
Current release5.3.6, November 202311.0, December 20223.5.1, February 20237.3.0, May 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercial inforestricted free version is availableOpen Source infoGPL version 2, commercial licence availablecommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C++Java
Server operating systemsAll OS with a Java VMLinux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
macOS
Windows
Data schemeschema-freeschema-free infoSchema can be enforcedyesschema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or dateyesyesnoyes
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.yes infothe object must implement a serialization strategyyesno infoImport/export of XML data possible
Secondary indexesyesyesyes infofull-text index on all search fieldsyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLSQL-like query languageyes infoSQL92SQL-like query language (SphinxQL)Yes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
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
Proprietary protocolGraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
Supported programming languages.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresyes infoEvent Listeners, Executor Servicesyes infovia XQuery or JavaScriptnouser defined functions and aggregates, HTTP Server extensions in Java
Triggersyes infoEventsyesnoyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supportednone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated MapyesnoneMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyImmediate Consistency in HA-Cluster
Foreign keys infoReferential integritynononoyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataone or two-phase-commit; repeatable reads; read commitedACID infocan act as a resource manager in an XA/JTA transactionnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes, with Range Indexesyes
User concepts infoAccess controlRole-based access controlRole-based access control at the document and subdocument levelsnoAccess rights for users and roles

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More resources
HazelcastMarkLogicSphinxStardog
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