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DBMS > MarkLogic vs. Sphinx vs. Splice Machine

System Properties Comparison MarkLogic vs. Sphinx vs. Splice Machine

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Editorial information provided by DB-Engines
NameMarkLogic  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionOperational and transactional Enterprise NoSQL databaseOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Search engineRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score11.73
Rank#41  Overall
#7  Document stores
#1  Native XML DBMS
#1  RDF stores
#4  Search engines
Score6.34
Rank#60  Overall
#7  Search engines
Score0.79
Rank#190  Overall
#93  Relational DBMS
Websitewww.marklogic.comsphinxsearch.comsplicemachine.com
Technical documentationdocs.marklogic.comsphinxsearch.com/­docsdoc.splicemachine.com
DeveloperMarkLogic Corp.Sphinx Technologies Inc.Splice Machine
Initial release200120012014
Current release9.0, 20173.2.1, January 20202.0
License infoCommercial or Open Sourcecommercial inforestricted free version is availableOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++Java
Server operating systemsLinux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-free infoSchema can be enforcedyesyes
Typing infopredefined data types such as float or dateyesnoyes
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
Secondary indexesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLyes infoSQL92SQL-like query language (SphinxQL)yes
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
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesC
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
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infovia XQuery or JavaScriptnoyes infoJava
Triggersyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneMulti-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 jobsnoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infocan act as a resource manager in an XA/JTA transactionnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyes 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.yes, with Range Indexesyes
User concepts infoAccess controlRole-based access control at the document and subdocument levelsnoAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
MarkLogicSphinxSplice Machine
Specific characteristicsThe MarkLogic Multi-Model Database provides the simplest way to integrate data from...
» more
THE ONLY SCALE-OUT SQL RDBMS WITH BUILT-IN MACHINE LEARNING For data-rich, real-time...
» more
Competitive advantagesThe main benefit of MarkLogic is simplicity. By making things simpler, MarkLogic...
» more
Operational Workloads: Full ACID support with high performance at scale Multi-row...
» more
Typical application scenariosMarkLogic’s main use case is the Operational Data Hub . A Data Hub is useful for...
» more
New AI/ML and IoT Applications Data Warehouse Offloads Application Modernization...
» more
Key customersMarkLogic has proven results managing mission-critical data with over 1,000 global...
» more
Market metricsMarkLogic is well known within the Fortune 1000, with a strong presence in financial...
» more
Licensing and pricing modelsMarkLogic provides a variety of licenses and cloud services: MarkLogic Data Hub Service...
» more
Kubernetes Community Edition: https://hub.helm.sh/charts/splicemachine/splice-helm...
» more
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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