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DBMS > AllegroGraph vs. Google Cloud Datastore vs. Hive vs. Microsoft Access

System Properties Comparison AllegroGraph vs. Google Cloud Datastore vs. Hive vs. Microsoft Access

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Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHive  Xexclude from comparisonMicrosoft Access  Xexclude from comparison
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platformdata warehouse software for querying and managing large distributed datasets, built on HadoopMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Document storeRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.13
Rank#179  Overall
#30  Document stores
#17  Graph DBMS
#7  RDF stores
#7  Vector DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score101.16
Rank#11  Overall
#8  Relational DBMS
Websiteallegrograph.comcloud.google.com/­datastorehive.apache.orgwww.microsoft.com/­en-us/­microsoft-365/­access
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmlcloud.google.com/­datastore/­docscwiki.apache.org/­confluence/­display/­Hive/­Homedeveloper.microsoft.com/­en-us/­access
DeveloperFranz Inc.GoogleApache Software Foundation infoinitially developed by FacebookMicrosoft
Initial release2004200820121992
Current release8.0, December 20233.1.3, April 20221902 (16.0.11328.20222), March 2019
License infoCommercial or Open Sourcecommercial infoLimited community edition freecommercialOpen Source infoApache Version 2commercial infoBundled with Microsoft Office
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++
Server operating systemsLinux
OS X
Windows
hostedAll OS with a Java VMWindows infoNot a real database server, but making use of DLLs
Data schemeyes infoRDF schemasschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes, details hereyesyes
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.no infobulk load of XML files possibleno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSPARQL is used as query languageSQL-like query language (GQL)SQL-like DML and DDL statementsyes infobut not compliant to any SQL standard
APIs and other access methodsRESTful HTTP API
SPARQL
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
ADO.NET
DAO
ODBC
OLE DB
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
PHP
Python
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lispusing Google App Engineyes infouser defined functions and integration of map-reduceyes infosince Access 2010 using the ACE-engine
TriggersyesCallbacks using the Google Apps Enginenoyes infosince Access 2010 using the ACE-engine
Partitioning methods infoMethods for storing different data on different nodeswith FederationShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication using Paxosselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate 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 Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID infobut no files for transaction logging
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infobut no files for transaction logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and rolesno infoa simple user-level security was built in till version Access 2003
More information provided by the system vendor
AllegroGraphGoogle Cloud DatastoreHiveMicrosoft Access
Specific characteristicsKnowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more
Competitive advantagesAllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more
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