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DBMS > Amazon Neptune vs. Fujitsu Enterprise Postgres vs. Google Cloud Datastore vs. Microsoft Access

System Properties Comparison Amazon Neptune vs. Fujitsu Enterprise Postgres vs. Google Cloud Datastore vs. Microsoft Access

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Access  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudEnterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformMicrosoft 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 modelGraph DBMS
RDF store
Relational DBMSDocument storeRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.20
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score0.22
Rank#304  Overall
#137  Relational DBMS
Score4.13
Rank#71  Overall
#12  Document stores
Score93.76
Rank#12  Overall
#8  Relational DBMS
Websiteaws.amazon.com/­neptunewww.postgresql.fastware.comcloud.google.com/­datastorewww.microsoft.com/­en-us/­microsoft-365/­access
Technical documentationaws.amazon.com/­neptune/­developer-resourceswww.postgresql.fastware.com/­product-manualscloud.google.com/­datastore/­docsdeveloper.microsoft.com/­en-us/­access
DeveloperAmazonPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyGoogleMicrosoft
Initial release201720081992
Current releaseFujitsu Enterprise Postgres 14, January 20221902 (16.0.11328.20222), March 2019
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercial infoBundled with Microsoft Office
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC++
Server operating systemshostedLinux
Windows
hostedWindows infoNot a real database server, but making use of DLLs
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes, details hereyes
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 indexesnoyesyesyes
SQL infoSupport of SQLnoyesSQL-like query language (GQL)yes infobut not compliant to any SQL standard
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
DAO
ODBC
OLE DB
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Server-side scripts infoStored proceduresnouser defined functionsusing Google App Engineyes infosince Access 2010 using the ACE-engine
TriggersnoyesCallbacks using the Google Apps Engineyes infosince Access 2010 using the ACE-engine
Partitioning methods infoMethods for storing different data on different nodesnonepartitioning by range, list and by hashShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.Source-replica replicationMulti-source replication using Paxosnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate 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.
Foreign keys infoReferential integrityyes infoRelationships in graphsyesyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infobut no files for transaction logging
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyes 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.no
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)fine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no infoa simple user-level security was built in till version Access 2003

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More resources
Amazon NeptuneFujitsu Enterprise PostgresGoogle Cloud DatastoreMicrosoft Access
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