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

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

Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonHive  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.A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwaredata warehouse software for querying and managing large distributed datasets, built on HadoopFully 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 DBMSRelational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.10
Rank#126  Overall
#61  Relational DBMS
Score62.59
Rank#18  Overall
#12  Relational DBMS
Score0.69
Rank#234  Overall
#107  Relational DBMS
Score0.54
Rank#255  Overall
#116  Relational DBMS
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
hive.apache.orgwww.kinetica.comsplicemachine.com
Technical documentationdocs.heavy.aicwiki.apache.org/­confluence/­display/­Hive/­Homedocs.kinetica.comsplicemachine.com/­how-it-works
DeveloperDrizzle project, originally started by Brian AkerHEAVY.AI, Inc.Apache Software Foundation infoinitially developed by FacebookKineticaSplice Machine
Initial release20082016201220122014
Current release7.2.4, September 20125.10, January 20223.1.3, April 20227.1, August 20213.1, March 2021
License infoCommercial or Open SourceOpen Source infoGNU GPLOpen Source infoApache Version 2; enterprise edition availableOpen Source infoApache Version 2commercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++ and CUDAJavaC, C++Java
Server operating systemsFreeBSD
Linux
OS X
LinuxAll OS with a Java VMLinuxLinux
OS X
Solaris
Windows
Data schemeyesyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.nono
Secondary indexesyesnoyesyesyes
SQL infoSupport of SQLyes infowith proprietary extensionsyesSQL-like DML and DDL statementsSQL-like DML and DDL statementsyes
APIs and other access methodsJDBCJDBC
ODBC
Thrift
Vega
JDBC
ODBC
Thrift
JDBC
ODBC
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C++
Java
PHP
All languages supporting JDBC/ODBC/Thrift
Python
C++
Java
PHP
Python
C++
Java
JavaScript (Node.js)
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnonoyes infouser defined functions and integration of map-reduceuser 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 nodesShardingSharding infoRound robinShardingShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replicationselectable replication factorSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoquery execution via MapReducenoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyesnonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnononoACID
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.yesyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPfine grained access rights according to SQL-standardAccess rights for users, groups and rolesAccess rights for users and roles on table levelAccess rights for users, groups and roles according to SQL-standard

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More resources
DrizzleHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022HiveKineticaSplice Machine
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