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DBMS > Amazon Aurora vs. EXASOL vs. Hazelcast vs. IBM Db2 Event Store vs. Splice Machine

System Properties Comparison Amazon Aurora vs. EXASOL vs. Hazelcast vs. IBM Db2 Event Store vs. Splice Machine

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonEXASOL  Xexclude from comparisonHazelcast  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.A widely adopted in-memory data gridDistributed Event Store optimized for Internet of Things use casesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSRelational DBMSKey-value storeEvent Store
Time Series DBMS
Relational DBMS
Secondary database modelsDocument storeDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.50
Rank#49  Overall
#31  Relational DBMS
Score2.25
Rank#120  Overall
#57  Relational DBMS
Score6.87
Rank#55  Overall
#6  Key-value stores
Score0.23
Rank#316  Overall
#2  Event Stores
#28  Time Series DBMS
Score0.54
Rank#255  Overall
#116  Relational DBMS
Websiteaws.amazon.com/­rds/­aurorawww.exasol.comhazelcast.comwww.ibm.com/­products/­db2-event-storesplicemachine.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlwww.exasol.com/­resourceshazelcast.org/­imdg/­docswww.ibm.com/­docs/­en/­db2-event-storesplicemachine.com/­how-it-works
DeveloperAmazonExasolHazelcastIBMSplice Machine
Initial release20152000200820172014
Current release5.3.6, November 20232.03.1, March 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2; commercial licenses availablecommercial infofree developer edition availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC and C++Java
Server operating systemshostedAll OS with a Java VMLinux infoLinux, macOS, Windows for the developer additionLinux
OS X
Solaris
Windows
Data schemeyesyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.yesnoyes infothe object must implement a serialization strategyno
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLyesyesSQL-like query languageyes infothrough the embedded Spark runtimeyes
APIs and other access methodsADO.NET
JDBC
ODBC
.Net
JDBC
ODBC
WebSocket
JCache
JPA
Memcached protocol
RESTful HTTP API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Java
Lua
Python
R
.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++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyesuser defined functionsyes infoEvent Listeners, Executor Servicesyesyes infoJava
Triggersyesyesyes infoEventsnoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infoReplicated MapActive-active shard replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoHadoop integrationyesnoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDone or two-phase-commit; repeatable reads; read commitednoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesNo - written data is immutableyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesYes - 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.yesyesyesyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standardRole-based access controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon AuroraEXASOLHazelcastIBM Db2 Event StoreSplice Machine
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