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DBMS > Datomic vs. Hazelcast vs. Linter vs. VoltDB

System Properties Comparison Datomic vs. Hazelcast vs. Linter vs. VoltDB

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonHazelcast  Xexclude from comparisonLinter  Xexclude from comparisonVoltDB  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 gridRDBMS for high security requirementsDistributed In-Memory NewSQL RDBMS infoUsed for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory
Primary database modelRelational DBMSKey-value storeRelational DBMSRelational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.55
Rank#144  Overall
#67  Relational DBMS
Score5.72
Rank#59  Overall
#6  Key-value stores
Score0.03
Rank#368  Overall
#156  Relational DBMS
Score1.38
Rank#156  Overall
#72  Relational DBMS
Websitewww.datomic.comhazelcast.comlinter.ruwww.voltdb.com
Technical documentationdocs.datomic.comhazelcast.org/­imdg/­docsdocs.voltdb.com
DeveloperCognitectHazelcastrelex.ruVoltDB Inc.
Initial release2012200819902010
Current release1.0.7180, July 20245.3.6, November 202311.3, April 2022
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoAGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureJavaC and C++Java, C++
Server operating systemsAll OS with a Java VMAll OS with a Java VMAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Linux
OS X infofor development
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 infoonly a subset of SQL 99
APIs and other access methodsRESTful HTTP APIJCache
JPA
Memcached protocol
RESTful HTTP API
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
Java API
JDBC
RESTful HTTP/JSON API
Supported programming languagesClojure
Java
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
C#
C++
Erlang infonot officially supported
Go
Java
JavaScript infoNode.js
PHP
Python
Server-side scripts infoStored proceduresyes infoTransaction Functionsyes infoEvent Listeners, Executor Servicesyes infoproprietary syntax with the possibility to convert from PL/SQLJava
TriggersBy using transaction functionsyes infoEventsyesno
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersyes infoReplicated MapSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
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 integritynonoyesno infoFOREIGN KEY constraints are not supported
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitedACIDACID infoTransactions are executed single-threaded within stored procedures
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoData access is serialized by the server
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes infoSnapshots and command logging
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 developmentyes
User concepts infoAccess controlnoRole-based access controlfine grained access rights according to SQL-standardUsers and roles with access to stored procedures

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More resources
DatomicHazelcastLinterVoltDB
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