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DBMS > Databricks vs. Greenplum vs. HEAVY.AI vs. Kinetica vs. PouchDB

System Properties Comparison Databricks vs. Greenplum vs. HEAVY.AI vs. Kinetica vs. PouchDB

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGreenplum  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonKinetica  Xexclude from comparisonPouchDB  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.Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.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 CPUsJavaScript DBMS with an API inspired by CouchDB
Primary database modelDocument store
Relational DBMS
Relational DBMSRelational DBMSRelational DBMSDocument store
Secondary database modelsDocument store
Spatial DBMS
Spatial DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score8.08
Rank#48  Overall
#31  Relational DBMS
Score1.64
Rank#145  Overall
#67  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score2.34
Rank#112  Overall
#21  Document stores
Websitewww.databricks.comgreenplum.orggithub.com/­heavyai/­heavydb
www.heavy.ai
www.kinetica.compouchdb.com
Technical documentationdocs.databricks.comdocs.greenplum.orgdocs.heavy.aidocs.kinetica.compouchdb.com/­guides
DeveloperDatabricksPivotal Software Inc.HEAVY.AI, Inc.KineticaApache Software Foundation
Initial release20132005201620122012
Current release7.0.0, September 20235.10, January 20227.1, August 20217.1.1, June 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache Version 2; enterprise edition availablecommercialOpen Source
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++ and CUDAC, C++JavaScript
Server operating systemshostedLinuxLinuxLinuxserver-less, requires a JavaScript environment (browser, Node.js)
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.yesyes infosince Version 4.2nonono
Secondary indexesyesyesnoyesyes infovia views
SQL infoSupport of SQLwith Databricks SQLyesyesSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
JDBC
ODBC
Thrift
Vega
JDBC
ODBC
RESTful HTTP API
HTTP REST infoonly for PouchDB Server
JavaScript API
Supported programming languagesPython
R
Scala
C
Java
Perl
Python
R
All languages supporting JDBC/ODBC/Thrift
Python
C++
Java
JavaScript (Node.js)
Python
JavaScript
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesnouser defined functionsView functions in JavaScript
Triggersyesnoyes 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 robinShardingSharding infowith a proxy-based framework, named couchdb-lounge
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationMulti-source replicationSource-replica replicationMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Foreign keys infoReferential integrityyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backend
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardAccess rights for users and roles on table levelno
More information provided by the system vendor
DatabricksGreenplumHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022KineticaPouchDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksGreenplumHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022KineticaPouchDB
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