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DBMS > FatDB vs. Fujitsu Enterprise Postgres vs. Hazelcast vs. IBM Db2 Event Store

System Properties Comparison FatDB vs. Fujitsu Enterprise Postgres vs. Hazelcast vs. IBM Db2 Event Store

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonHazelcast  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionA .NET NoSQL DBMS that can integrate with and extend SQL Server.Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.A widely adopted in-memory data gridDistributed Event Store optimized for Internet of Things use cases
Primary database modelDocument store
Key-value store
Relational DBMSKey-value storeEvent Store
Time Series DBMS
Secondary database modelsDocument store
Spatial DBMS
Document store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.37
Rank#278  Overall
#128  Relational DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score0.27
Rank#309  Overall
#2  Event Stores
#28  Time Series DBMS
Websitewww.postgresql.fastware.comhazelcast.comwww.ibm.com/­products/­db2-event-store
Technical documentationwww.postgresql.fastware.com/­product-manualshazelcast.org/­imdg/­docswww.ibm.com/­docs/­en/­db2-event-store
DeveloperFatCloudPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyHazelcastIBM
Initial release201220082017
Current releaseFujitsu Enterprise Postgres 14, January 20225.3.6, November 20232.0
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2; commercial licenses availablecommercial infofree developer edition available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC#CJavaC and C++
Server operating systemsWindowsLinux
Windows
All OS with a Java VMLinux infoLinux, macOS, Windows for the developer addition
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.yes infothe object must implement a serialization strategyno
Secondary indexesyesyesyesno
SQL infoSupport of SQLno infoVia inetgration in SQL ServeryesSQL-like query languageyes infothrough the embedded Spark runtime
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JCache
JPA
Memcached protocol
RESTful HTTP API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC#.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
Server-side scripts infoStored proceduresyes infovia applicationsuser defined functionsyes infoEvent Listeners, Executor Servicesyes
Triggersyes infovia applicationsyesyes infoEventsno
Partitioning methods infoMethods for storing different data on different nodesShardingpartitioning by range, list and by hashShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationyes infoReplicated MapActive-active shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDone or two-phase-commit; repeatable reads; read commitedno
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesNo - written data is immutable
Durability infoSupport for making data persistentyesyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlno infoCan implement custom security layer via applicationsfine grained access rights according to SQL-standardRole-based access controlfine grained access rights according to SQL-standard
More information provided by the system vendor
FatDBFujitsu Enterprise PostgresHazelcastIBM Db2 Event Store
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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More resources
FatDBFujitsu Enterprise PostgresHazelcastIBM Db2 Event Store
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