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DBMS > Graph Engine vs. Hazelcast vs. IBM Db2 Event Store vs. JaguarDB

System Properties Comparison Graph Engine vs. Hazelcast vs. IBM Db2 Event Store vs. JaguarDB

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Editorial information provided by DB-Engines
NameGraph Engine infoformer name: Trinity  Xexclude from comparisonHazelcast  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonJaguarDB  Xexclude from comparison
DescriptionA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineA widely adopted in-memory data gridDistributed Event Store optimized for Internet of Things use casesPerformant, highly scalable DBMS for AI and IoT applications
Primary database modelGraph DBMS
Key-value store
Key-value storeEvent Store
Time Series DBMS
Key-value store
Vector DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score5.97
Rank#57  Overall
#6  Key-value stores
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
#13  Vector DBMS
Websitewww.graphengine.iohazelcast.comwww.ibm.com/­products/­db2-event-storewww.jaguardb.com
Technical documentationwww.graphengine.io/­docs/­manualhazelcast.org/­imdg/­docswww.ibm.com/­docs/­en/­db2-event-storewww.jaguardb.com/­support.html
DeveloperMicrosoftHazelcastIBMDataJaguar, Inc.
Initial release2010200820172015
Current release5.3.6, November 20232.03.3 July 2023
License infoCommercial or Open SourceOpen Source infoMIT LicenseOpen Source infoApache Version 2; commercial licenses availablecommercial infofree developer edition availableOpen Source infoGPL V3.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation language.NET and CJavaC and C++C++ infothe server part. Clients available in other languages
Server operating systems.NETAll OS with a Java VMLinux infoLinux, macOS, Windows for the developer additionLinux
Data schemeyesschema-freeyesyes
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.noyes infothe object must implement a serialization strategynono
Secondary indexesyesnoyes
SQL infoSupport of SQLnoSQL-like query languageyes infothrough the embedded Spark runtimeA subset of ANSI SQL is implemented infobut no views, foreign keys, triggers
APIs and other access methodsRESTful HTTP APIJCache
JPA
Memcached protocol
RESTful HTTP API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Supported programming languagesC#
C++
F#
Visual Basic
.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
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyesyes infoEvent Listeners, Executor Servicesyesno
Triggersnoyes infoEventsnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated MapActive-active shard replicationMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoone or two-phase-commit; repeatable reads; read commitednono
Concurrency infoSupport for concurrent manipulation of datayesyesNo - written data is immutableyes
Durability infoSupport for making data persistentoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesno
User concepts infoAccess controlRole-based access controlfine grained access rights according to SQL-standardrights management via user accounts

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More resources
Graph Engine infoformer name: TrinityHazelcastIBM Db2 Event StoreJaguarDB
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