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DBMS > gStore vs. Spark SQL vs. Sphinx vs. XTDB

System Properties Comparison gStore vs. Spark SQL vs. Sphinx vs. XTDB

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Editorial information provided by DB-Engines
NamegStore  Xexclude from comparisonSpark SQL  Xexclude from comparisonSphinx  Xexclude from comparisonXTDB infoformerly named Crux  Xexclude from comparison
DescriptionA native Graph DBMS to store and maintain very large RDF datasets.Spark SQL is a component on top of 'Spark Core' for structured data processingOpen source search engine for searching in data from different sources, e.g. relational databasesA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelGraph DBMS
RDF store
Relational DBMSSearch engineDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.04
Rank#359  Overall
#37  Graph DBMS
#18  RDF stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.11
Rank#343  Overall
#46  Document stores
Websiteen.gstore.cnspark.apache.org/­sqlsphinxsearch.comgithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationen.gstore.cn/­#/­enDocsspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docswww.xtdb.com/­docs
DeveloperApache Software FoundationSphinx Technologies Inc.Juxt Ltd.
Initial release2016201420012019
Current release1.2, November 20233.5.0 ( 2.13), September 20233.5.1, February 20231.19, September 2021
License infoCommercial or Open SourceOpen Source infoBSDOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence availableOpen Source infoMIT License
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ScalaC++Clojure
Server operating systemsLinuxLinux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
All OS with a Java 8 (and higher) VM
Linux
Data schemeschema-free and OWL/RDFS-schema supportyesyesschema-free
Typing infopredefined data types such as float or dateyesyesnoyes, extensible-data-notation format
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.nonono
Secondary indexesnoyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsSQL-like query language (SphinxQL)limited SQL, making use of Apache Calcite
APIs and other access methodsHTTP API
SPARQL 1.1
JDBC
ODBC
Proprietary protocolHTTP REST
JDBC
Supported programming languagesC++
Java
JavaScript (Node.js)
PHP
Python
Java
Python
R
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Clojure
Java
Server-side scripts infoStored proceduresyesnonono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CoreSharding infoPartitioning is done manually, search queries against distributed index is supportednone
Replication methods infoMethods for redundantly storing data on multiple nodesnonenoneyes, each node contains all data
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnonoACID
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, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlUsers, roles and permissions, Role-Based Access Control (RBAC) supportednono

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More resources
gStoreSpark SQLSphinxXTDB infoformerly named Crux
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