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DBMS > Datomic vs. Hazelcast vs. HyperSQL vs. Splice Machine

System Properties Comparison Datomic vs. Hazelcast vs. HyperSQL vs. Splice Machine

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonHazelcast  Xexclude from comparisonHyperSQL infoalso known as HSQLDB  Xexclude from comparisonSplice Machine  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 gridMultithreaded, transactional RDBMS written in Java infoalso known as HSQLDBOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSKey-value storeRelational 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
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score3.49
Rank#87  Overall
#47  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.datomic.comhazelcast.comhsqldb.orgsplicemachine.com
Technical documentationdocs.datomic.comhazelcast.org/­imdg/­docshsqldb.org/­web/­hsqlDocsFrame.htmlsplicemachine.com/­how-it-works
DeveloperCognitectHazelcastSplice Machine
Initial release2012200820012014
Current release1.0.6735, June 20235.3.6, November 20232.7.2, June 20233.1, March 2021
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoApache Version 2; commercial licenses availableOpen Source infobased on BSD licenseOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureJavaJavaJava
Server operating systemsAll OS with a Java VMAll OS with a Java VMAll OS with a Java VM infoEmbedded (into Java applications) and Client-Server operating modesLinux
OS X
Solaris
Windows
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 strategyno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLnoSQL-like query languageyesyes
APIs and other access methodsRESTful HTTP APIJCache
JPA
Memcached protocol
RESTful HTTP API
HTTP API infoJDBC via HTTP
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
Supported programming languagesClojure
Java
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
All languages supporting JDBC/ODBC
Java
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infoTransaction Functionsyes infoEvent Listeners, Executor ServicesJava, SQLyes infoJava
TriggersBy using transaction functionsyes infoEventsyesyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingnoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersyes infoReplicated MapnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoYes, via Full Spark Integration
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 integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitedACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
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 developmentyesyesyes
User concepts infoAccess controlnoRole-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
DatomicHazelcastHyperSQL infoalso known as HSQLDBSplice Machine
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