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DBMS > Fujitsu Enterprise Postgres vs. Google Cloud Datastore vs. Ingres vs. Spark SQL

System Properties Comparison Fujitsu Enterprise Postgres vs. Google Cloud Datastore vs. Ingres vs. Spark SQL

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Editorial information provided by DB-Engines
NameFujitsu Enterprise Postgres  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonIngres  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionEnterprise-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 PlatformWell established RDBMSSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSDocument storeRelational DBMSRelational DBMS
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
Score3.80
Rank#82  Overall
#44  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.postgresql.fastware.comcloud.google.com/­datastorewww.actian.com/­databases/­ingresspark.apache.org/­sql
Technical documentationwww.postgresql.fastware.com/­product-manualscloud.google.com/­datastore/­docsdocs.actian.com/­ingresspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyGoogleActian CorporationApache Software Foundation
Initial release20081974 infooriginally developed at University Berkely in early 1970s2014
Current releaseFujitsu Enterprise Postgres 14, January 202211.2, May 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCCScala
Server operating systemsLinux
Windows
hostedAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
Linux
OS X
Windows
Data schemeyesschema-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.nono infobut tools for importing/exporting data from/to XML-files availableno
Secondary indexesyesyesyesno
SQL infoSupport of SQLyesSQL-like query language (GQL)yesSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
JDBC
ODBC
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsusing Google App Engineyesno
TriggersyesCallbacks using the Google Apps Engineyesno
Partitioning methods infoMethods for storing different data on different nodespartitioning by range, list and by hashShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslyyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication using PaxosIngres Replicatornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDno
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyes infoMVCCyes
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.nonono
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardno

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More resources
Fujitsu Enterprise PostgresGoogle Cloud DatastoreIngresSpark SQL
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