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DBMS > MarkLogic vs. Microsoft Azure AI Search vs. Sadas Engine vs. Splice Machine

System Properties Comparison MarkLogic vs. Microsoft Azure AI Search vs. Sadas Engine vs. Splice Machine

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Editorial information provided by DB-Engines
NameMarkLogic  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonSadas Engine  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionOperational and transactional Enterprise NoSQL databaseSearch-as-a-service for web and mobile app developmentSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsOpen-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 DBMSRelational DBMS
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.92
Rank#58  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#6  Search engines
Score5.59
Rank#63  Overall
#7  Search engines
Score0.00
Rank#383  Overall
#158  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.marklogic.comazure.microsoft.com/­en-us/­services/­searchwww.sadasengine.comsplicemachine.com
Technical documentationdocs.marklogic.comlearn.microsoft.com/­en-us/­azure/­searchwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationsplicemachine.com/­how-it-works
DeveloperMarkLogic Corp.MicrosoftSADAS s.r.l.Splice Machine
Initial release2001201520062014
Current release11.0, December 2022V18.03.1, March 2021
License infoCommercial or Open Sourcecommercial inforestricted free version is availablecommercialcommercial infofree trial version availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++Java
Server operating systemsLinux
OS X
Windows
hostedAIX
Linux
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-free infoSchema can be enforcedyesyesyes
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.yesnono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyes infoSQL92noyesyes
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
RESTful HTTP APIJDBC
ODBC
Proprietary protocol
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
Java
JavaScript
Python
.Net
C
C#
C++
Groovy
Java
PHP
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infovia XQuery or JavaScriptnonoyes infoJava
Triggersyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicehorizontal partitioningShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoImplicit feature of the cloud servicenoneMulti-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 jobsnonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
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 datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes, with Range Indexesnoyes infomanaged by 'Learn by Usage'yes
User concepts infoAccess controlRole-based access control at the document and subdocument levelsyes infousing Azure authenticationAccess rights for users, groups and roles according to SQL-standardAccess rights for users, groups and roles according to SQL-standard

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More resources
MarkLogicMicrosoft Azure AI SearchSadas EngineSplice Machine
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