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DBMS > Badger vs. Citus vs. Spark SQL

System Properties Comparison Badger vs. Citus vs. Spark SQL

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonCitus  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeRelational DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­dgraph-io/­badgerwww.citusdata.comspark.apache.org/­sql
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.citusdata.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDGraph LabsApache Software Foundation
Initial release201720102014
Current release8.1, December 20183.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoAGPL, commercial license also availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoCScala
Server operating systemsBSD
Linux
OS X
Solaris
Windows
LinuxLinux
OS X
Windows
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or datenoyesyes
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 infospecific XML type available, but no XML query functionalityno
Secondary indexesnoyesno
SQL infoSupport of SQLnoyes infostandard, with numerous extensionsSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Supported programming languagesGo.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.no
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replication infoother methods possible by using 3rd party extensionsnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlnofine grained access rights according to SQL-standardno

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More resources
BadgerCitusSpark SQL
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