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DBMS > Badger vs. Databricks vs. FatDB vs. Hyprcubd

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

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonDatabricks  Xexclude from comparisonFatDB  Xexclude from comparisonHyprcubd  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines 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.A .NET NoSQL DBMS that can integrate with and extend SQL Server.Serverless Time Series DBMS
Primary database modelKey-value storeDocument store
Relational DBMS
Document store
Key-value store
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#320  Overall
#47  Key-value stores
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Websitegithub.com/­dgraph-io/­badgerwww.databricks.comhyprcubd.com (offline)
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.databricks.com
DeveloperDGraph LabsDatabricksFatCloudHyprcubd, Inc.
Initial release201720132012
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC#Go
Server operating systemsBSD
Linux
OS X
Solaris
Windows
hostedWindowshosted
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)schema-freeyes
Typing infopredefined data types such as float or datenoyesyes infotime, int, uint, float, string
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.noyesno
Secondary indexesnoyesyesno
SQL infoSupport of SQLnowith Databricks SQLno infoVia inetgration in SQL ServerSQL-like query language
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
gRPC (https)
Supported programming languagesGoPython
R
Scala
C#
Server-side scripts infoStored proceduresnouser defined functions and aggregatesyes infovia applicationsno
Triggersnoyes infovia applicationsno
Partitioning methods infoMethods for storing different data on different nodesnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyesselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesno
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.nonono
User concepts infoAccess controlnono infoCan implement custom security layer via applicationstoken access
More information provided by the system vendor
BadgerDatabricksFatDBHyprcubd
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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BadgerDatabricksFatDBHyprcubd
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