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DBMS > Badger vs. Databricks vs. EJDB vs. FatDB

System Properties Comparison Badger vs. Databricks vs. EJDB vs. FatDB

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonDatabricks  Xexclude from comparisonEJDB  Xexclude from comparisonFatDB  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.The 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)A .NET NoSQL DBMS that can integrate with and extend SQL Server.
Primary database modelKey-value storeDocument store
Relational DBMS
Document storeDocument store
Key-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.27
Rank#297  Overall
#44  Document stores
Websitegithub.com/­dgraph-io/­badgerwww.databricks.comgithub.com/­Softmotions/­ejdb
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.databricks.comgithub.com/­Softmotions/­ejdb/­blob/­master/­README.md
DeveloperDGraph LabsDatabricksSoftmotionsFatCloud
Initial release2017201320122012
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoGPLv2commercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoCC#
Server operating systemsBSD
Linux
OS X
Solaris
Windows
hostedserver-lessWindows
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free
Typing infopredefined data types such as float or datenoyes infostring, integer, double, bool, date, object_idyes
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.noyes
Secondary indexesnoyesnoyes
SQL infoSupport of SQLnowith Databricks SQLnono infoVia inetgration in SQL Server
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
in-process shared library.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
Supported programming languagesGoPython
R
Scala
Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
C#
Server-side scripts infoStored proceduresnouser defined functions and aggregatesnoyes infovia applications
Triggersnonoyes infovia applications
Partitioning methods infoMethods for storing different data on different nodesnonenoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyesnoneselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynono infotypically not needed, however similar functionality with collection joins possibleno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes 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.nono
User concepts infoAccess controlnonono infoCan implement custom security layer via applications
More information provided by the system vendor
BadgerDatabricksEJDBFatDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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BadgerDatabricksEJDBFatDB
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