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DBMS > Apache Jena - TDB vs. GeoSpock vs. GridGain vs. Microsoft Azure Data Explorer

System Properties Comparison Apache Jena - TDB vs. GeoSpock vs. GridGain vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
NameApache Jena - TDB  Xexclude from comparisonGeoSpock  Xexclude from comparisonGridGain  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionA RDF storage and query DBMS, shipped as an optional-use component of the Apache Jena frameworkSpatial and temporal data processing engine for extreme data scaleGridGain is an in-memory computing platform, built on Apache IgniteFully managed big data interactive analytics platform
Primary database modelRDF storeRelational DBMSKey-value store
Relational DBMS
Relational DBMS infocolumn oriented
Secondary database modelsTime Series DBMSDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.75
Rank#84  Overall
#3  RDF stores
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websitejena.apache.org/­documentation/­tdb/­index.htmlgeospock.comwww.gridgain.comazure.microsoft.com/­services/­data-explorer
Technical documentationjena.apache.org/­documentation/­tdb/­index.htmlwww.gridgain.com/­docs/­index.htmldocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software Foundation infooriginally developed by HP LabsGeoSpockGridGain Systems, Inc.Microsoft
Initial release200020072019
Current release4.9.0, July 20232.0, September 2019GridGain 8.5.1cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache License, Version 2.0commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava, JavascriptJava, C++, .Net
Server operating systemsAll OS with a Java VMhostedLinux
OS X
Solaris
Windows
hosted
Data schemeyes infoRDF SchemasyesyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
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.noyesyes
Secondary indexesyestemporal, categoricalyesall fields are automatically indexed
SQL infoSupport of SQLnoANSI SQL for query only (using Presto)ANSI-99 for query and DML statements, subset of DDLKusto Query Language (KQL), SQL subset
APIs and other access methodsFuseki infoREST-style SPARQL HTTP Interface
Jena RDF API
RIO infoRDF Input/Output
JDBCHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesJavaC#
C++
Java
PHP
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyesnoyes (compute grid and cache interceptors can be used instead)Yes, possible languages: KQL, Python, R
Triggersyes infovia event handlernoyes (cache interceptors and events)yes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesnoneAutomatic shardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes (replicated cache)yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes (compute grid and hadoop accelerator)Spark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoTDB TransactionsnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.noyesno
User concepts infoAccess controlAccess control via Jena SecurityAccess rights for users can be defined per tableSecurity Hooks for custom implementationsAzure Active Directory Authentication

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More resources
Apache Jena - TDBGeoSpockGridGainMicrosoft Azure Data Explorer
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