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DBMS > Databricks vs. FoundationDB vs. Geode vs. Kinetica

System Properties Comparison Databricks vs. FoundationDB vs. Geode vs. Kinetica

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonFoundationDB  Xexclude from comparisonGeode  Xexclude from comparisonKinetica  Xexclude from comparison
Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the 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.Ordered key-value store. Core features are complimented by layers.Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesFully vectorized database across both GPUs and CPUs
Primary database modelDocument store
Relational DBMS
Document store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Key-value storeRelational DBMS
Secondary database modelsSpatial 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
Score1.03
Rank#190  Overall
#31  Document stores
#28  Key-value stores
#89  Relational DBMS
Score1.92
Rank#131  Overall
#23  Key-value stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Websitewww.databricks.comgithub.com/­apple/­foundationdbgeode.apache.orgwww.kinetica.com
Technical documentationdocs.databricks.comapple.github.io/­foundationdbgeode.apache.org/­docsdocs.kinetica.com
DeveloperDatabricksFoundationDBOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.Kinetica
Initial release2013201320022012
Current release6.2.28, November 20201.1, February 20177.1, August 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache Version 2; commercial licenses available as Gemfirecommercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC, C++
Server operating systemshostedLinux
OS X
Windows
All OS with a Java VM infothe JDK (8 or later) is also requiredLinux
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-free infosome layers support schemasschema-freeyes
Typing infopredefined data types such as float or dateno infosome layers support typingyesyes
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.yesnono
Secondary indexesyesnonoyes
SQL infoSupport of SQLwith Databricks SQLsupported in specific SQL layer onlySQL-like query language (OQL)SQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Java Client API
Memcached protocol
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesPython
R
Scala
.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
.Net
All JVM based languages
C++
Groovy
Java
Scala
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesin SQL-layer onlyuser defined functionsuser defined functions
Triggersnoyes infoCache Event Listenersyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesMulti-source replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyLinearizable consistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityin SQL-layer onlynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDyes, on a single nodeno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
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 controlnoAccess rights per client and object definableAccess rights for users and roles on table level
More information provided by the system vendor
DatabricksFoundationDBGeodeKinetica
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksFoundationDBGeodeKinetica
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