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DBMS > Datomic vs. Drizzle vs. Oracle Berkeley DB vs. Splice Machine vs. SQL.JS

System Properties Comparison Datomic vs. Drizzle vs. Oracle Berkeley DB vs. Splice Machine vs. SQL.JS

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonDrizzle  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSplice Machine  Xexclude from comparisonSQL.JS  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.Widely used in-process key-value storeOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkPort of SQLite to JavaScript
Primary database modelRelational DBMSRelational DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score0.53
Rank#252  Overall
#116  Relational DBMS
Websitewww.datomic.comwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlsplicemachine.comsql.js.org
Technical documentationdocs.datomic.comdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlsplicemachine.com/­how-it-workssql.js.org/­documentation/­index.html
DeveloperCognitectDrizzle project, originally started by Brian AkerOracle infooriginally developed by Sleepycat, which was acquired by OracleSplice MachineAlon Zakai infoenhancements implemented by others
Initial release20122008199420142012
Current release1.0.6735, June 20237.2.4, September 201218.1.40, May 20203.1, March 2021
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoGNU GPLOpen Source infocommercial license availableOpen Source infoAGPL 3.0, commercial license availableOpen Source
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureC++C, Java, C++ (depending on the Berkeley DB edition)JavaJavaScript
Server operating systemsAll OS with a Java VMFreeBSD
Linux
OS X
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Solaris
Windows
server-less, requires a JavaScript environment (browser, Node.js)
Data schemeyesyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesnoyesyes
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 infoonly with the Berkeley DB XML editionno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLnoyes infowith proprietary extensionsyes infoSQL interfaced based on SQLite is availableyesyes infoSQL-92 is not fully supported
APIs and other access methodsRESTful HTTP APIJDBCJDBC
Native Spark Datasource
ODBC
JavaScript API
Supported programming languagesClojure
Java
C
C++
Java
PHP
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
JavaScript
Server-side scripts infoStored proceduresyes infoTransaction Functionsnonoyes infoJavano
TriggersBy using transaction functionsno infohooks for callbacks inside the server can be used.yes infoonly for the SQL APIyesno
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingnoneShared Nothhing Auto-Sharding, Columnar Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replication
Source-replica replication
Source-replica replicationMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistencynone
Foreign keys infoReferential integritynoyesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyesno infoexcept by serializing a db to a file
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 controlnoPluggable authentication mechanisms infoe.g. LDAP, HTTPnoAccess rights for users, groups and roles according to SQL-standardno

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More resources
DatomicDrizzleOracle Berkeley DBSplice MachineSQL.JS
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