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DBMS > Databricks vs. Drizzle vs. HEAVY.AI vs. Kinetica vs. LevelDB

System Properties Comparison Databricks vs. Drizzle vs. HEAVY.AI vs. Kinetica vs. LevelDB

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonDrizzle  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonKinetica  Xexclude from comparisonLevelDB  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.
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.MySQL 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 values
Primary database modelDocument store
Relational DBMS
Relational DBMSRelational DBMSRelational DBMSKey-value store
Secondary database modelsSpatial DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
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
Websitewww.databricks.comgithub.com/­heavyai/­heavydb
www.heavy.ai
www.kinetica.comgithub.com/­google/­leveldb
Technical documentationdocs.databricks.comdocs.heavy.aidocs.kinetica.comgithub.com/­google/­leveldb/­blob/­main/­doc/­index.md
DeveloperDatabricksDrizzle project, originally started by Brian AkerHEAVY.AI, Inc.KineticaGoogle
Initial release20132008201620122011
Current release7.2.4, September 20125.10, January 20227.1, August 20211.23, February 2021
License infoCommercial or Open SourcecommercialOpen Source infoGNU GPLOpen Source infoApache Version 2; enterprise edition availablecommercialOpen Source infoBSD
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++ and CUDAC, C++C++
Server operating systemshostedFreeBSD
Linux
OS X
LinuxLinuxIllumos
Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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.yesnonono
Secondary indexesyesyesnoyesno
SQL infoSupport of SQLwith Databricks SQLyes infowith proprietary extensionsyesSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBCJDBC
ODBC
Thrift
Vega
JDBC
ODBC
RESTful HTTP API
Supported programming languagesPython
R
Scala
C
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
Server-side scripts infoStored proceduresuser defined functions and aggregatesnonouser defined functionsno
Triggersno infohooks for callbacks inside the server can be used.noyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoRound robinShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
Multi-source replicationSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infowith automatic compression on writes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPfine grained access rights according to SQL-standardAccess rights for users and roles on table levelno
More information provided by the system vendor
DatabricksDrizzleHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022KineticaLevelDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksDrizzleHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022KineticaLevelDB
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