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DBMS > EsgynDB vs. Fujitsu Enterprise Postgres vs. GridDB vs. Sadas Engine

System Properties Comparison EsgynDB vs. Fujitsu Enterprise Postgres vs. GridDB vs. Sadas Engine

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonGridDB  Xexclude from comparisonSadas Engine  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionEnterprise-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 DataSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments
Primary database modelRelational DBMSRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Key-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score0.31
Rank#285  Overall
#129  Relational DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score0.00
Rank#383  Overall
#158  Relational DBMS
Websitewww.esgyn.cnwww.postgresql.fastware.comgriddb.netwww.sadasengine.com
Technical documentationwww.postgresql.fastware.com/­product-manualsdocs.griddb.netwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentation
DeveloperEsgynPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyToshiba CorporationSADAS s.r.l.
Initial release201520132006
Current releaseFujitsu Enterprise Postgres 14, January 20225.1, August 20228.0
License infoCommercial or Open SourcecommercialcommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercial infofree trial version available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaCC++C++
Server operating systemsLinuxLinux
Windows
LinuxAIX
Linux
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 SQLyesyesSQL92, SQL-like TQL (Toshiba Query Language)yes
APIs and other access methodsADO.NET
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
Proprietary protocol
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.Net.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C
C#
C++
Groovy
Java
PHP
Python
Server-side scripts infoStored proceduresJava Stored Proceduresuser defined functionsnono
Triggersnoyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingpartitioning by range, list and by hashShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersSource-replica replicationSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoConnector 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 ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integrityyesyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID at container level
Concurrency infoSupport for concurrent manipulation of datayesyes, 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.noyesyes infomanaged by 'Learn by Usage'
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardAccess rights for users can be defined per databaseAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
EsgynDBFujitsu Enterprise PostgresGridDBSadas Engine
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
EsgynDBFujitsu Enterprise PostgresGridDBSadas Engine
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