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DBMS > Databricks vs. EJDB vs. FoundationDB vs. Oracle Berkeley DB

System Properties Comparison Databricks vs. EJDB vs. FoundationDB vs. Oracle Berkeley DB

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonEJDB  Xexclude from comparisonFoundationDB  Xexclude from comparisonOracle Berkeley DB  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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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.Embeddable document-store database library with JSON representation of queries (in MongoDB style)Ordered key-value store. Core features are complimented by layers.Widely used in-process key-value store
Primary database modelDocument store
Relational DBMS
Document storeDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Key-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.31
Rank#296  Overall
#44  Document stores
Score1.06
Rank#185  Overall
#31  Document stores
#28  Key-value stores
#85  Relational DBMS
Score2.01
Rank#126  Overall
#21  Key-value stores
#3  Native XML DBMS
Websitewww.databricks.comgithub.com/­Softmotions/­ejdbgithub.com/­apple/­foundationdbwww.oracle.com/­database/­technologies/­related/­berkeleydb.html
Technical documentationdocs.databricks.comgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mdapple.github.io/­foundationdbdocs.oracle.com/­cd/­E17076_05/­html/­index.html
DeveloperDatabricksSoftmotionsFoundationDBOracle infooriginally developed by Sleepycat, which was acquired by Oracle
Initial release2013201220131994
Current release6.2.28, November 202018.1.40, May 2020
License infoCommercial or Open SourcecommercialOpen Source infoGPLv2Open Source infoApache 2.0Open Source infocommercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC++C, Java, C++ (depending on the Berkeley DB edition)
Server operating systemshostedserver-lessLinux
OS X
Windows
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free infosome layers support schemasschema-free
Typing infopredefined data types such as float or dateyes infostring, integer, double, bool, date, object_idno infosome layers support typingno
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 infoonly with the Berkeley DB XML edition
Secondary indexesyesnonoyes
SQL infoSupport of SQLwith Databricks SQLnosupported in specific SQL layer onlyyes infoSQL interfaced based on SQLite is available
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
in-process shared library
Supported programming languagesPython
R
Scala
Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoin SQL-layer onlyno
Triggersnonoyes infoonly for the SQL API
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyLinearizable consistency
Foreign keys infoReferential integrityno infotypically not needed, however similar functionality with collection joins possiblein SQL-layer onlyno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/Write Lockingyes
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.noyes
User concepts infoAccess controlnonono
More information provided by the system vendor
DatabricksEJDBFoundationDBOracle Berkeley DB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksEJDBFoundationDBOracle Berkeley DB
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