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DBMS > Drizzle vs. ITTIA vs. Spark SQL vs. Splice Machine vs. SQL.JS

System Properties Comparison Drizzle vs. ITTIA vs. Spark SQL vs. Splice Machine vs. SQL.JS

Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonITTIA  Xexclude from comparisonSpark SQL  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.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Edge Time Series DBMS with Real-Time Stream ProcessingSpark SQL is a component on top of 'Spark Core' for structured data processingOpen-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 DBMSTime Series DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.39
Rank#273  Overall
#24  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score0.53
Rank#252  Overall
#116  Relational DBMS
Websitewww.ittia.comspark.apache.org/­sqlsplicemachine.comsql.js.org
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsplicemachine.com/­how-it-workssql.js.org/­documentation/­index.html
DeveloperDrizzle project, originally started by Brian AkerITTIA L.L.C.Apache Software FoundationSplice MachineAlon Zakai infoenhancements implemented by others
Initial release20082007201420142012
Current release7.2.4, September 20128.73.5.0 ( 2.13), September 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialOpen Source infoApache 2.0Open 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 languageC++C and C++ScalaJavaJavaScript
Server operating systemsFreeBSD
Linux
OS X
Linux
Windows
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
server-less, requires a JavaScript environment (browser, Node.js)
Data schemeyesFixed schemayesyesyes
Typing infopredefined data types such as float or dateyesFloat/Blob/Integer/String/Unicode/Date/Time/Timestamp/Intervalyesyesyes
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.nonono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLyes infowith proprietary extensionsyesSQL-like DML and DDL statementsyesyes infoSQL-92 is not fully supported
APIs and other access methodsJDBCJDBC
ODBC
RESTful HTTP API
WebSocket
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
JavaScript API
Supported programming languagesC
C++
Java
PHP
C
C++
JavaScript (Node.js)
Python
Java
Python
R
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
JavaScript
Server-side scripts infoStored proceduresnoyesnoyes infoJavano
Triggersno infohooks for callbacks inside the server can be used.nonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark CoreShared Nothhing Auto-Sharding, Columnar Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesnoneMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistencynone
Foreign keys infoReferential integrityyesyesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyesno 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.yesnoyesyes
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPDatabase file passwordsnoAccess rights for users, groups and roles according to SQL-standardno

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More resources
DrizzleITTIASpark SQLSplice MachineSQL.JS
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