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DBMS > Firebird vs. Fujitsu Enterprise Postgres vs. Google Cloud Datastore vs. HugeGraph

System Properties Comparison Firebird vs. Fujitsu Enterprise Postgres vs. Google Cloud Datastore vs. HugeGraph

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Editorial information provided by DB-Engines
NameFirebird  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHugeGraph  Xexclude from comparison
DescriptionFirebird is an open source RDBMS forked from Borland's InterBaseEnterprise-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 PlatformA fast-speed and highly-scalable Graph DBMS
Primary database modelRelational DBMSRelational DBMSDocument storeGraph DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score20.50
Rank#30  Overall
#18  Relational DBMS
Score0.37
Rank#278  Overall
#128  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score0.17
Rank#335  Overall
#31  Graph DBMS
Websitewww.firebirdsql.orgwww.postgresql.fastware.comcloud.google.com/­datastoregithub.com/­hugegraph
hugegraph.apache.org
Technical documentationwww.firebirdsql.org/­en/­reference-manualswww.postgresql.fastware.com/­product-manualscloud.google.com/­datastore/­docshugegraph.apache.org/­docs
DeveloperFirebird FoundationPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyGoogleBaidu
Initial release2000 infoAs fork of Borland's InterBase20082018
Current release5.0.0, January 2024Fujitsu Enterprise Postgres 14, January 20220.9
License infoCommercial or Open SourceOpen Source infoInitial Developer's Public LicensecommercialcommercialOpen Source infoApache Version 2.0
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 and C++CJava
Server operating systemsAIX
FreeBSD
HP-UX
Linux
OS X
server-less infoFirebird Embedded Server
Solaris
Unix
Windows
Linux
Windows
hostedLinux
macOS
Unix
Data schemeyesyesschema-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 indexesyesyesyesyes infoalso supports composite index and range index
SQL infoSupport of SQLyesyesSQL-like query language (GQL)no
APIs and other access methodsADO.NET
C/C++ API
JDBC infoJaybird
ODBC
OLE DB
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RESTful HTTP API
TinkerPop Gremlin
Supported programming languagesC
C#
C++
Delphi
Java
JavaScript infoNode.js
Lua
Perl
PHP
Python
Ruby
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Groovy
Java
Python
Server-side scripts infoStored proceduresPSQLuser defined functionsusing Google App Engineasynchronous Gremlin script jobs
TriggersyesyesCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesnonepartitioning by range, list and by hashShardingyes infodepending on used storage backend, e.g. Cassandra and HBase
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replicationMulti-source replication using Paxosyes infodepending on used storage backend, e.g. Cassandra and HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowvia hugegraph-spark
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.Eventual Consistency
Foreign keys infoReferential integrityyesyesyes infovia ReferenceProperties or Ancestor pathsyes infoedges in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayes infoFeatures a multi-generational MVCC architecture, readers do not block writersyes, 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 controlUsers with fine-grained authorization conceptfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users, roles and permissions

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More resources
FirebirdFujitsu Enterprise PostgresGoogle Cloud DatastoreHugeGraph
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