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DBMS > Databricks vs. HEAVY.AI vs. jBASE vs. Kinetica vs. Riak KV

System Properties Comparison Databricks vs. HEAVY.AI vs. jBASE vs. Kinetica vs. Riak KV

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonjBASE  Xexclude from comparisonKinetica  Xexclude from comparisonRiak KV  Xexclude from comparison
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.A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareA robust multi-value DBMS comprising development tools and middlewareFully vectorized database across both GPUs and CPUsDistributed, fault tolerant key-value store
Primary database modelDocument store
Relational DBMS
Relational DBMSMultivalue DBMSRelational DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexes
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
Score1.41
Rank#159  Overall
#3  Multivalue DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score4.10
Rank#82  Overall
#9  Key-value stores
Websitewww.databricks.comgithub.com/­heavyai/­heavydb
www.heavy.ai
www.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-jbasewww.kinetica.com
Technical documentationdocs.databricks.comdocs.heavy.aidocs.rocketsoftware.com/­bundle?labelkey=jbase_5.9docs.kinetica.comwww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperDatabricksHEAVY.AI, Inc.Rocket Software (formerly Zumasys)KineticaOpenSource, formerly Basho Technologies
Initial release20132016199120122009
Current release5.10, January 20225.77.1, August 20213.2.0, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; enterprise edition availablecommercialcommercialOpen Source infoApache version 2, commercial enterprise edition
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ and CUDAC, C++Erlang
Server operating systemshostedLinuxAIX
Linux
Windows
LinuxLinux
OS X
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesoptionalyesno
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.yesnoyesnono
Secondary indexesyesnoyesrestricted
SQL infoSupport of SQLwith Databricks SQLyesEmbedded SQL for jBASE in BASICSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Thrift
Vega
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API
JDBC
ODBC
RESTful HTTP API
HTTP API
Native Erlang Interface
Supported programming languagesPython
R
Scala
All languages supporting JDBC/ODBC/Thrift
Python
.Net
Basic
Jabbascript
Java
C++
Java
JavaScript (Node.js)
Python
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoyesuser defined functionsErlang
Triggersnoyesyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinShardingShardingSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replicationyesSource-replica replicationselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Foreign keys infoReferential integritynonoyesno infolinks between data sets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.noyesyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights can be defined down to the item levelAccess rights for users and roles on table levelyes, using Riak Security
More information provided by the system vendor
DatabricksHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022jBASEKineticaRiak KV
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022jBASEKineticaRiak KV
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