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DBMS > Databricks vs. FoundationDB vs. jBASE vs. Kinetica vs. LevelDB

System Properties Comparison Databricks vs. FoundationDB vs. jBASE vs. Kinetica vs. LevelDB

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonFoundationDB  Xexclude from comparisonjBASE  Xexclude from comparisonKinetica  Xexclude from comparisonLevelDB  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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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.A robust multi-value DBMS comprising development tools and middlewareFully 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
Document store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Multivalue DBMSRelational DBMSKey-value store
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
Score1.41
Rank#159  Overall
#3  Multivalue DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score2.35
Rank#111  Overall
#19  Key-value stores
Websitewww.databricks.comgithub.com/­apple/­foundationdbwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-jbasewww.kinetica.comgithub.com/­google/­leveldb
Technical documentationdocs.databricks.comapple.github.io/­foundationdbdocs.rocketsoftware.com/­bundle?labelkey=jbase_5.9docs.kinetica.comgithub.com/­google/­leveldb/­blob/­main/­doc/­index.md
DeveloperDatabricksFoundationDBRocket Software (formerly Zumasys)KineticaGoogle
Initial release20132013199120122011
Current release6.2.28, November 20205.77.1, August 20211.23, February 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialcommercialOpen 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, C++C++
Server operating systemshostedLinux
OS X
Windows
AIX
Linux
Windows
LinuxIllumos
Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-free infosome layers support schemasschema-freeyesschema-free
Typing infopredefined data types such as float or dateno infosome layers support typingoptionalyesno
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.yesyesnono
Secondary indexesyesnoyesno
SQL infoSupport of SQLwith Databricks SQLsupported in specific SQL layer onlyEmbedded SQL for jBASE in BASICSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesPython
R
Scala
.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
.Net
Basic
Jabbascript
Java
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 aggregatesin SQL-layer onlyyesuser defined functionsno
Triggersnoyesyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesyesSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyLinearizable consistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityin SQL-layer onlynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDnono
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 controlnoAccess rights can be defined down to the item levelAccess rights for users and roles on table levelno
More information provided by the system vendor
DatabricksFoundationDBjBASEKineticaLevelDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksFoundationDBjBASEKineticaLevelDB
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