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DBMS > FatDB vs. Fujitsu Enterprise Postgres vs. Google Cloud Datastore vs. Stardog

System Properties Comparison FatDB vs. Fujitsu Enterprise Postgres vs. Google Cloud Datastore vs. Stardog

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonStardog  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionA .NET NoSQL DBMS that can integrate with and extend SQL Server.Enterprise-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 PlatformEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelDocument store
Key-value store
Relational DBMSDocument storeGraph DBMS
RDF store
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.37
Rank#278  Overall
#128  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score2.07
Rank#122  Overall
#11  Graph DBMS
#6  RDF stores
Websitewww.postgresql.fastware.comcloud.google.com/­datastorewww.stardog.com
Technical documentationwww.postgresql.fastware.com/­product-manualscloud.google.com/­datastore/­docsdocs.stardog.com
DeveloperFatCloudPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyGoogleStardog-Union
Initial release201220082010
Current releaseFujitsu Enterprise Postgres 14, January 20227.3.0, May 2020
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#CJava
Server operating systemsWindowsLinux
Windows
hostedLinux
macOS
Windows
Data schemeschema-freeyesschema-freeschema-free and OWL/RDFS-schema support
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 infoImport/export of XML data possible
Secondary indexesyesyesyesyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLno infoVia inetgration in SQL ServeryesSQL-like query language (GQL)Yes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
Supported programming languagesC#.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresyes infovia applicationsuser defined functionsusing Google App Engineuser defined functions and aggregates, HTTP Server extensions in Java
Triggersyes infovia applicationsyesCallbacks using the Google Apps Engineyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesShardingpartitioning by range, list and by hashShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationMulti-source replication using PaxosMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate 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.Immediate Consistency in HA-Cluster
Foreign keys infoReferential integritynoyesyes infovia ReferenceProperties or Ancestor pathsyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes
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.noyes
User concepts infoAccess controlno infoCan implement custom security layer via applicationsfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles

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More resources
FatDBFujitsu Enterprise PostgresGoogle Cloud DatastoreStardog
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