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DBMS > Fujitsu Enterprise Postgres vs. Google Cloud Datastore vs. ObjectBox vs. TimescaleDB

System Properties Comparison Fujitsu Enterprise Postgres vs. Google Cloud Datastore vs. ObjectBox vs. TimescaleDB

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Editorial information provided by DB-Engines
NameFujitsu Enterprise Postgres  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonObjectBox  Xexclude from comparisonTimescaleDB  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 PlatformExtremely fast embedded database for small devices, IoT and MobileA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSDocument storeObject oriented DBMSTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.31
Rank#285  Overall
#129  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score1.20
Rank#170  Overall
#5  Object oriented DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitewww.postgresql.fastware.comcloud.google.com/­datastoreobjectbox.iowww.timescale.com
Technical documentationwww.postgresql.fastware.com/­product-manualscloud.google.com/­datastore/­docsdocs.objectbox.iodocs.timescale.com
DeveloperPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyGoogleObjectBox LimitedTimescale
Initial release200820172017
Current releaseFujitsu Enterprise Postgres 14, January 20222.15.0, May 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache License 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC and C++C
Server operating systemsLinux
Windows
hostedAndroid
iOS
Linux
macOS
Windows
Linux
OS X
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes, details hereyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.nonoyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyesSQL-like query language (GQL)noyes infofull PostgreSQL SQL syntax
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
Proprietary native APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functionsusing Google App Enginenouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
TriggersyesCallbacks using the Google Apps Enginenoyes
Partitioning methods infoMethods for storing different data on different nodespartitioning by range, list and by hashShardingnoneyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication using Paxosonline/offline synchronization between client and serverSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
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 ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyes
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)yesfine grained access rights according to SQL-standard
More information provided by the system vendor
Fujitsu Enterprise PostgresGoogle Cloud DatastoreObjectBoxTimescaleDB
Specific characteristics100% compatible with community PostgreSQL
» more
Competitive advantagesBuilt-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more
Typical application scenariosTransactional payments applications, reporting and mixed workloads.
» more
Market metricsOver 30 years experience in database technology. Over 20 years in Postgres development...
» more
Licensing and pricing modelsCore based licensing
» more
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Fujitsu Enterprise PostgresGoogle Cloud DatastoreObjectBoxTimescaleDB
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