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DBMS > GeoSpock vs. GridGain vs. Microsoft Azure SQL Database vs. Spark SQL vs. Stardog

System Properties Comparison GeoSpock vs. GridGain vs. Microsoft Azure SQL Database vs. Spark SQL vs. Stardog

Editorial information provided by DB-Engines
NameGeoSpock  Xexclude from comparisonGridGain  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonSpark SQL  Xexclude from comparisonStardog  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionSpatial and temporal data processing engine for extreme data scaleGridGain is an in-memory computing platform, built on Apache IgniteDatabase as a Service offering with high compatibility to Microsoft SQL ServerSpark SQL is a component on top of 'Spark Core' for structured data processingEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMSRelational DBMSGraph DBMS
RDF store
Secondary database modelsTime Series DBMSDocument store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score76.78
Rank#16  Overall
#11  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score2.07
Rank#122  Overall
#11  Graph DBMS
#6  RDF stores
Websitegeospock.comwww.gridgain.comazure.microsoft.com/­en-us/­products/­azure-sql/­databasespark.apache.org/­sqlwww.stardog.com
Technical documentationwww.gridgain.com/­docs/­index.htmldocs.microsoft.com/­en-us/­azure/­azure-sqlspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.stardog.com
DeveloperGeoSpockGridGain Systems, Inc.MicrosoftApache Software FoundationStardog-Union
Initial release2007201020142010
Current release2.0, September 2019GridGain 8.5.1V123.5.0 ( 2.13), September 20237.3.0, May 2020
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache 2.0commercial 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 serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, JavascriptJava, C++, .NetC++ScalaJava
Server operating systemshostedLinux
OS X
Solaris
Windows
hostedLinux
OS X
Windows
Linux
macOS
Windows
Data schemeyesyesyesyesschema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.noyesyesnono infoImport/export of XML data possible
Secondary indexestemporal, categoricalyesyesnoyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLANSI SQL for query only (using Presto)ANSI-99 for query and DML statements, subset of DDLyesSQL-like DML and DDL statementsYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsJDBCHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
ADO.NET
JDBC
ODBC
JDBC
ODBC
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresnoyes (compute grid and cache interceptors can be used instead)Transact SQLnouser defined functions and aggregates, HTTP Server extensions in Java
Triggersnoyes (cache interceptors and events)yesnoyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)yes, with always 3 replicas availablenoneMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency in HA-Cluster
Foreign keys infoReferential integritynonoyesnoyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlAccess rights for users can be defined per tableSecurity Hooks for custom implementationsfine grained access rights according to SQL-standardnoAccess rights for users and roles

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More resources
GeoSpockGridGainMicrosoft Azure SQL Database infoformerly SQL AzureSpark SQLStardog
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