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DBMS > searchxml vs. Spark SQL vs. Yaacomo

System Properties Comparison searchxml vs. Spark SQL vs. Yaacomo

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Editorial information provided by DB-Engines
Namesearchxml  Xexclude from comparisonSpark SQL  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionDBMS for structured and unstructured content wrapped with an application serverSpark SQL is a component on top of 'Spark Core' for structured data processingOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelNative XML DBMS
Search engine
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.00
Rank#383  Overall
#7  Native XML DBMS
#25  Search engines
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.searchxml.net/­category/­productsspark.apache.org/­sqlyaacomo.com
Technical documentationwww.searchxml.net/­support/­handoutsspark.apache.org/­docs/­latest/­sql-programming-guide.html
Developerinformationpartners gmbhApache Software FoundationQ2WEB GmbH
Initial release201520142009
Current release1.03.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Scala
Server operating systemsWindowsLinux
OS X
Windows
Android
Linux
Windows
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes
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 indexesyesnoyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyes
APIs and other access methodsRESTful HTTP API
WebDAV
XQuery
XSLT
JDBC
ODBC
JDBC
ODBC
Supported programming languagesC++ infomost other programming languages supported via APIsJava
Python
R
Scala
Server-side scripts infoStored proceduresyes infoon the application serverno
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesnoneyes, utilizing Spark Corehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infosychronisation to multiple collectionsnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
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 datamultiple readers, single writernoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlDomain, group and role-based access control at the document level and for application servicesnofine grained access rights according to SQL-standard

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More resources
searchxmlSpark SQLYaacomo
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