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

System Properties Comparison Drizzle vs. HEAVY.AI vs. Kinetica vs. LevelDB 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 comparisonKinetica  Xexclude from comparisonLevelDB  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 hardwareFully vectorized database across both GPUs and CPUsEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSRelational DBMSRelational DBMSKey-value storeRelational DBMS
Secondary database modelsSpatial DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score2.35
Rank#111  Overall
#19  Key-value stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
www.kinetica.comgithub.com/­google/­leveldbsplicemachine.com
Technical documentationdocs.heavy.aidocs.kinetica.comgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdsplicemachine.com/­how-it-works
DeveloperDrizzle project, originally started by Brian AkerHEAVY.AI, Inc.KineticaGoogleSplice Machine
Initial release20082016201220112014
Current release7.2.4, September 20125.10, January 20227.1, August 20211.23, February 20213.1, March 2021
License infoCommercial or Open SourceOpen Source infoGNU GPLOpen Source infoApache Version 2; enterprise edition availablecommercialOpen Source infoBSDOpen 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 CUDAC, C++C++Java
Server operating systemsFreeBSD
Linux
OS X
LinuxLinuxIllumos
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeyesyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesnoyes
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 indexesyesnoyesnoyes
SQL infoSupport of SQLyes infowith proprietary extensionsyesSQL-like DML and DDL statementsnoyes
APIs and other access methodsJDBCJDBC
ODBC
Thrift
Vega
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
JavaScript (Node.js)
Python
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnonouser defined functionsnoyes infoJava
Triggersno infohooks for callbacks inside the server can be used.noyes infotriggers when inserted values for one or more columns fall within a specified rangenoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoRound robinShardingnoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replicationSource-replica replicationnoneMulti-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 Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesnoyes
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 persistentyesyesyesyes infowith automatic compression on writesyes
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 and roles on table levelnoAccess 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 2022KineticaLevelDBSplice Machine
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