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DBMS > Drizzle vs. Fauna vs. HEAVY.AI vs. Kinetica vs. Splice Machine

System Properties Comparison Drizzle vs. Fauna vs. HEAVY.AI vs. Kinetica vs. Splice Machine

Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonFauna infopreviously named FaunaDB  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonKinetica  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.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareFully vectorized database across both GPUs and CPUsOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSDocument store
Graph DBMS
Relational DBMS
Time Series DBMS
Relational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.55
Rank#154  Overall
#26  Document stores
#14  Graph DBMS
#72  Relational DBMS
#13  Time Series DBMS
Score2.10
Rank#126  Overall
#61  Relational DBMS
Score0.69
Rank#234  Overall
#107  Relational DBMS
Score0.54
Rank#255  Overall
#116  Relational DBMS
Websitefauna.comgithub.com/­heavyai/­heavydb
www.heavy.ai
www.kinetica.comsplicemachine.com
Technical documentationdocs.fauna.comdocs.heavy.aidocs.kinetica.comsplicemachine.com/­how-it-works
DeveloperDrizzle project, originally started by Brian AkerFauna, Inc.HEAVY.AI, Inc.KineticaSplice Machine
Initial release20082014201620122014
Current release7.2.4, September 20125.10, January 20227.1, August 20213.1, March 2021
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialOpen Source infoApache Version 2; enterprise edition availablecommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ScalaC++ and CUDAC, C++Java
Server operating systemsFreeBSD
Linux
OS X
hostedLinuxLinuxLinux
OS X
Solaris
Windows
Data schemeyesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesnoyesyesyes
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 indexesyesyesnoyesyes
SQL infoSupport of SQLyes infowith proprietary extensionsnoyesSQL-like DML and DDL statementsyes
APIs and other access methodsJDBCRESTful HTTP APIJDBC
ODBC
Thrift
Vega
JDBC
ODBC
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C++
Java
PHP
C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift
All languages supporting JDBC/ODBC/Thrift
Python
C++
Java
JavaScript (Node.js)
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functionsnouser defined functionsyes infoJava
Triggersno infohooks for callbacks inside the server can be used.nonoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infoconsistent hashingSharding infoRound robinShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replicationMulti-source replicationSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyesyesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPIdentity management, authentication, and access controlfine grained access rights according to SQL-standardAccess rights for users and roles on table levelAccess rights for users, groups and roles according to SQL-standard

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More resources
DrizzleFauna infopreviously named FaunaDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022KineticaSplice Machine
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