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DBMS > Fujitsu Enterprise Postgres vs. Google Cloud Bigtable vs. GridDB vs. ITTIA

System Properties Comparison Fujitsu Enterprise Postgres vs. Google Cloud Bigtable vs. GridDB vs. ITTIA

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Editorial information provided by DB-Engines
NameFujitsu Enterprise Postgres  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGridDB  Xexclude from comparisonITTIA  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.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Scalable in-memory time series database optimized for IoT and Big DataEdge Time Series DBMS with Real-Time Stream Processing
Primary database modelRelational DBMSKey-value store
Wide column store
Time Series DBMSTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
Key-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.37
Rank#278  Overall
#128  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score0.44
Rank#267  Overall
#23  Time Series DBMS
Websitewww.postgresql.fastware.comcloud.google.com/­bigtablegriddb.netwww.ittia.com
Technical documentationwww.postgresql.fastware.com/­product-manualscloud.google.com/­bigtable/­docsdocs.griddb.net
DeveloperPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyGoogleToshiba CorporationITTIA L.L.C.
Initial release201520132007
Current releaseFujitsu Enterprise Postgres 14, January 20225.1, August 20228.7
License infoCommercial or Open SourcecommercialcommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC++C and C++
Server operating systemsLinux
Windows
hostedLinuxLinux
Windows
Data schemeyesschema-freeyesFixed schema
Typing infopredefined data types such as float or dateyesnoyes infonumerical, string, blob, geometry, boolean, timestampFloat/Blob/Integer/String/Unicode/Date/Time/Timestamp/Interval
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.nonono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLyesnoSQL92, SQL-like TQL (Toshiba Query Language)yes
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
WebSocket
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Python
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C++
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functionsnonoyes
Triggersyesnoyesno
Partitioning methods infoMethods for storing different data on different nodespartitioning by range, list and by hashShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACID at container levelyes
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyes, multi-version concurrency control (MVCC)
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.noyesyes
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)Access rights for users can be defined per databaseDatabase file passwords
More information provided by the system vendor
Fujitsu Enterprise PostgresGoogle Cloud BigtableGridDBITTIA
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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Fujitsu Enterprise PostgresGoogle Cloud BigtableGridDBITTIA
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