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DBMS > Google Cloud Datastore vs. Hive vs. Microsoft Azure Synapse Analytics vs. RDF4J

System Properties Comparison Google Cloud Datastore vs. Hive vs. Microsoft Azure Synapse Analytics vs. RDF4J

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHive  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platformdata warehouse software for querying and managing large distributed datasets, built on HadoopElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelDocument storeRelational DBMSRelational DBMSRDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Websitecloud.google.com/­datastorehive.apache.orgazure.microsoft.com/­services/­synapse-analyticsrdf4j.org
Technical documentationcloud.google.com/­datastore/­docscwiki.apache.org/­confluence/­display/­Hive/­Homedocs.microsoft.com/­azure/­synapse-analyticsrdf4j.org/­documentation
DeveloperGoogleApache Software Foundation infoinitially developed by FacebookMicrosoftSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2008201220162004
Current release3.1.3, April 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++Java
Server operating systemshostedAll OS with a Java VMhostedLinux
OS X
Unix
Windows
Data schemeschema-freeyesyesyes infoRDF Schemas
Typing infopredefined data types such as float or dateyes, 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
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like DML and DDL statementsyesno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
ADO.NET
JDBC
ODBC
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
PHP
Python
C#
Java
PHP
Java
PHP
Python
Server-side scripts infoStored proceduresusing Google App Engineyes infouser defined functions and integration of map-reduceTransact SQLyes
TriggersCallbacks using the Google Apps Enginenonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding, horizontal partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosselectable replication factoryesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyes infoquery execution via MapReducenono
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.Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraints
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACIDACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoin-memory storage is supported as well
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and rolesyesno

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More resources
Google Cloud DatastoreHiveMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseRDF4J infoformerly known as Sesame
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