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DBMS > Datomic vs. Hazelcast vs. Microsoft Azure Table Storage vs. Splice Machine vs. UniData,UniVerse

System Properties Comparison Datomic vs. Hazelcast vs. Microsoft Azure Table Storage vs. Splice Machine vs. UniData,UniVerse

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonHazelcast  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonSplice Machine  Xexclude from comparisonUniData,UniVerse  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA widely adopted in-memory data gridA Wide Column Store for rapid development using massive semi-structured datasetsOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkMultiValue database and application server with SQL mapping layer and meta database capabilities
Primary database modelRelational DBMSKey-value storeWide column storeRelational DBMSMultivalue DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score4.48
Rank#75  Overall
#6  Wide column stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score3.16
Rank#97  Overall
#2  Multivalue DBMS
Websitewww.datomic.comhazelcast.comazure.microsoft.com/­en-us/­services/­storage/­tablessplicemachine.comwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-unidata
Technical documentationdocs.datomic.comhazelcast.org/­imdg/­docssplicemachine.com/­how-it-worksdocs.rocketsoftware.com/­bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata
DeveloperCognitectHazelcastMicrosoftSplice MachineRocket Software
Initial release20122008201220141985
Current release1.0.6735, June 20235.3.6, November 20233.1, March 2021
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoAGPL 3.0, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureJavaJavaC
Server operating systemsAll OS with a Java VMAll OS with a Java VMhostedLinux
OS X
Solaris
Windows
AIX
HP-UX
Linux
Solaris
Windows
Data schemeyesschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyesoptional
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 strategyno
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLnoSQL-like query languagenoyesyes
APIs and other access methodsRESTful HTTP APIJCache
JPA
Memcached protocol
RESTful HTTP API
RESTful HTTP APIJDBC
Native Spark Datasource
ODBC
Java API infoJPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API
Supported programming languagesClojure
Java
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
.Net
Basic infoU2 Basic
C
Java
Server-side scripts infoStored proceduresyes infoTransaction Functionsyes infoEvent Listeners, Executor Servicesnoyes infoJavayes
TriggersBy using transaction functionsyes infoEventsnoyesyes infoU2 Basic
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingSharding infoImplicit feature of the cloud serviceShared Nothhing Auto-Sharding, Columnar Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersyes infoReplicated Mapyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitedoptimistic lockingACIDACID infoconfigurable
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentyesnoyes
User concepts infoAccess controlnoRole-based access controlAccess rights based on private key authentication or shared access signaturesAccess rights for users, groups and roles according to SQL-standardAccess rights according to SQL-standard and operating system based

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DatomicHazelcastMicrosoft Azure Table StorageSplice MachineUniData,UniVerse
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