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DBMS > Badger vs. Databricks vs. Spark SQL vs. STSdb

System Properties Comparison Badger vs. Databricks vs. Spark SQL vs. STSdb

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonDatabricks  Xexclude from comparisonSpark SQL  Xexclude from comparisonSTSdb  Xexclude from comparison
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.Spark SQL is a component on top of 'Spark Core' for structured data processingKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelKey-value storeDocument store
Relational DBMS
Relational DBMSKey-value store
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
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.10
Rank#357  Overall
#51  Key-value stores
Websitegithub.com/­dgraph-io/­badgerwww.databricks.comspark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.databricks.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDGraph LabsDatabricksApache Software FoundationSTS Soft SC
Initial release2017201320142011
Current release3.5.0 ( 2.13), September 20234.0.8, September 2015
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoApache 2.0Open Source infoGPLv2, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoScalaC#
Server operating systemsBSD
Linux
OS X
Solaris
Windows
hostedLinux
OS X
Windows
Windows
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or datenoyesyes infoprimitive types and user defined types (classes)
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 indexesnoyesnono
SQL infoSupport of SQLnowith Databricks SQLSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
.NET Client API
Supported programming languagesGoPython
R
Scala
Java
Python
R
Scala
C#
Java
Server-side scripts infoStored proceduresnouser defined functions and aggregatesnono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesnoneyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnono
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.nonono
User concepts infoAccess controlnonono
More information provided by the system vendor
BadgerDatabricksSpark SQLSTSdb
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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BadgerDatabricksSpark SQLSTSdb
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