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

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

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonDrizzle  Xexclude from comparisonHazelcast  Xexclude from comparisonSplice Machine  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.A widely adopted in-memory data gridOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSRelational DBMSKey-value storeRelational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitewww.datomic.comhazelcast.comsplicemachine.com
Technical documentationdocs.datomic.comhazelcast.org/­imdg/­docssplicemachine.com/­how-it-works
DeveloperCognitectDrizzle project, originally started by Brian AkerHazelcastSplice Machine
Initial release2012200820082014
Current release1.0.6735, June 20237.2.4, September 20125.3.6, November 20233.1, March 2021
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoGNU GPLOpen Source infoApache Version 2; commercial licenses availableOpen 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, ClojureC++JavaJava
Server operating systemsAll OS with a Java VMFreeBSD
Linux
OS X
All OS with a Java VMLinux
OS X
Solaris
Windows
Data schemeyesyesschema-freeyes
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 strategy
Secondary indexesyesyesyesyes
SQL infoSupport of SQLnoyes infowith proprietary extensionsSQL-like query languageyes
APIs and other access methodsRESTful HTTP APIJDBCJCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesClojure
Java
C
C++
Java
PHP
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infoTransaction Functionsnoyes infoEvent Listeners, Executor Servicesyes infoJava
TriggersBy using transaction functionsno infohooks for callbacks inside the server can be used.yes infoEventsyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replication
Source-replica replication
yes infoReplicated MapMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesYes, 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 Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDone or two-phase-commit; repeatable reads; read commitedACID
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 developmentyesyes
User concepts infoAccess controlnoPluggable authentication mechanisms infoe.g. LDAP, HTTPRole-based access controlAccess rights for users, groups and roles according to SQL-standard

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DatomicDrizzleHazelcastSplice Machine
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