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DBMS > Hazelcast vs. IBM Db2 Event Store vs. Spark SQL vs. Transbase

System Properties Comparison Hazelcast vs. IBM Db2 Event Store vs. Spark SQL vs. Transbase

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Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionA widely adopted in-memory data gridDistributed Event Store optimized for Internet of Things use casesSpark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelKey-value storeEvent Store
Time Series DBMS
Relational DBMSRelational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.66
Rank#54  Overall
#5  Key-value stores
Score0.25
Rank#320  Overall
#2  Event Stores
#28  Time Series DBMS
Score19.56
Rank#34  Overall
#21  Relational DBMS
Score0.20
Rank#327  Overall
#144  Relational DBMS
Websitehazelcast.comwww.ibm.com/­products/­db2-event-storespark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.html
Technical documentationhazelcast.org/­imdg/­docswww.ibm.com/­docs/­en/­db2-event-storespark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperHazelcastIBMApache Software FoundationTransaction Software GmbH
Initial release2008201720141987
Current release5.3.6, November 20232.03.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercial infofree developer edition availableOpen Source infoApache 2.0commercial infofree development license
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++ScalaC and C++
Server operating systemsAll OS with a Java VMLinux infoLinux, macOS, Windows for the developer additionLinux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeschema-freeyesyesyes
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 strategynonono
Secondary indexesyesnonoyes
SQL infoSupport of SQLSQL-like query languageyes infothrough the embedded Spark runtimeSQL-like DML and DDL statementsyes
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languages.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
Java
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresyes infoEvent Listeners, Executor Servicesyesnoyes
Triggersyes infoEventsnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated MapActive-active shard replicationnoneSource-replica 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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataone or two-phase-commit; repeatable reads; read commitednonoyes
Concurrency infoSupport for concurrent manipulation of datayesNo - written data is immutableyesyes
Durability infoSupport for making data persistentyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnono
User concepts infoAccess controlRole-based access controlfine grained access rights according to SQL-standardnofine grained access rights according to SQL-standard

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More resources
HazelcastIBM Db2 Event StoreSpark SQLTransbase
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