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DBMS > Apache Jena - TDB vs. Google Cloud Datastore vs. Ingres vs. Microsoft Azure Synapse Analytics vs. TimesTen

System Properties Comparison Apache Jena - TDB vs. Google Cloud Datastore vs. Ingres vs. Microsoft Azure Synapse Analytics vs. TimesTen

Editorial information provided by DB-Engines
NameApache Jena - TDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonIngres  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonTimesTen  Xexclude from comparison
DescriptionA RDF storage and query DBMS, shipped as an optional-use component of the Apache Jena frameworkAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformWell established RDBMSElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerIn-Memory RDBMS compatible to Oracle
Primary database modelRDF storeDocument storeRelational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.62
Rank#83  Overall
#3  RDF stores
Score4.36
Rank#72  Overall
#12  Document stores
Score3.80
Rank#82  Overall
#44  Relational DBMS
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score1.36
Rank#161  Overall
#75  Relational DBMS
Websitejena.apache.org/­documentation/­tdb/­index.htmlcloud.google.com/­datastorewww.actian.com/­databases/­ingresazure.microsoft.com/­services/­synapse-analyticswww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationjena.apache.org/­documentation/­tdb/­index.htmlcloud.google.com/­datastore/­docsdocs.actian.com/­ingresdocs.microsoft.com/­azure/­synapse-analyticsdocs.oracle.com/­database/­timesten-18.1
DeveloperApache Software Foundation infooriginally developed by HP LabsGoogleActian CorporationMicrosoftOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release200020081974 infooriginally developed at University Berkely in early 1970s20161998
Current release4.9.0, July 202311.2, May 202211 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourceOpen Source infoApache License, Version 2.0commercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaCC++
Server operating systemsAll OS with a Java VMhostedAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
hostedAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeyes infoRDF Schemasschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyes, details hereyesyesyes
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.nono infobut tools for importing/exporting data from/to XML-files availablenono
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLnoSQL-like query language (GQL)yesyesyes
APIs and other access methodsFuseki infoREST-style SPARQL HTTP Interface
Jena RDF API
RIO infoRDF Input/Output
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
ADO.NET
JDBC
ODBC
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languagesJava.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
Java
PHP
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresyesusing Google App EngineyesTransact SQLPL/SQL
Triggersyes infovia event handlerCallbacks using the Google Apps Engineyesnono
Partitioning methods infoMethods for storing different data on different nodesnoneShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslySharding, horizontal partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication using PaxosIngres ReplicatoryesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoTDB TransactionsACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMVCCyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlAccess control via Jena SecurityAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardyesfine grained access rights according to SQL-standard

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More resources
Apache Jena - TDBGoogle Cloud DatastoreIngresMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseTimesTen
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