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DBMS > BigObject vs. Fujitsu Enterprise Postgres vs. GridDB vs. Realm

System Properties Comparison BigObject vs. Fujitsu Enterprise Postgres vs. GridDB vs. Realm

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Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonGridDB  Xexclude from comparisonRealm  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesEnterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.Scalable in-memory time series database optimized for IoT and Big DataA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedRelational DBMSTime Series DBMSDocument store
Secondary database modelsDocument store
Spatial DBMS
Key-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score0.31
Rank#285  Overall
#129  Relational DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score7.60
Rank#52  Overall
#9  Document stores
Websitebigobject.iowww.postgresql.fastware.comgriddb.netrealm.io
Technical documentationdocs.bigobject.iowww.postgresql.fastware.com/­product-manualsdocs.griddb.netrealm.io/­docs
DeveloperBigObject, Inc.PostgreSQL Global Development Group, Fujitsu Australia Software TechnologyToshiba CorporationRealm, acquired by MongoDB in May 2019
Initial release201520132014
Current releaseFujitsu Enterprise Postgres 14, January 20225.1, August 2022
License infoCommercial or Open Sourcecommercial infofree community edition availablecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC++
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
Linux
Windows
LinuxAndroid
Backend: server-less
iOS
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestampyes
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 indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesSQL92, SQL-like TQL (Toshiba Query Language)no
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Java infowith Android only
Objective-C
React Native
Swift
Server-side scripts infoStored proceduresLuauser defined functionsnono inforuns within the applications so server-side scripts are unnecessary
Triggersnoyesyesyes infoChange Listeners
Partitioning methods infoMethods for storing different data on different nodesnonepartitioning by range, list and by hashShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID at container levelACID
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yes, multi-version concurrency control (MVCC)yes
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.yesyesyes infoIn-Memory realm
User concepts infoAccess controlnofine grained access rights according to SQL-standardAccess rights for users can be defined per databaseyes
More information provided by the system vendor
BigObjectFujitsu Enterprise PostgresGridDBRealm
Specific characteristics100% compatible with community PostgreSQL
» more
GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantagesBuilt-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more
1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosTransactional payments applications, reporting and mixed workloads.
» more
Factory 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 metricsOver 30 years experience in database technology. Over 20 years in Postgres development...
» more
GitHub trending repository
» more
Licensing and pricing modelsCore based licensing
» more
Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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More resources
BigObjectFujitsu Enterprise PostgresGridDBRealm
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