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DBMS > Badger vs. Kinetica vs. Lovefield vs. Spark SQL

System Properties Comparison Badger vs. Kinetica vs. Lovefield vs. Spark SQL

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonKinetica  Xexclude from comparisonLovefield  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Fully vectorized database across both GPUs and CPUsEmbeddable relational database for web apps written in pure JavaScriptSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
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
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score0.33
Rank#286  Overall
#131  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­dgraph-io/­badgerwww.kinetica.comgoogle.github.io/­lovefieldspark.apache.org/­sql
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.kinetica.comgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDGraph LabsKineticaGoogleApache Software Foundation
Initial release2017201220142014
Current release7.1, August 20212.1.12, February 20173.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoC, C++JavaScriptScala
Server operating systemsBSD
Linux
OS X
Solaris
Windows
Linuxserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariLinux
OS X
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or datenoyesyesyes
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.nononono
Secondary indexesnoyesyesno
SQL infoSupport of SQLnoSQL-like DML and DDL statementsSQL-like query language infovia JavaScript builder patternSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Supported programming languagesGoC++
Java
JavaScript (Node.js)
Python
JavaScriptJava
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functionsnono
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeUsing read-only observersno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoGPU vRAM or System RAMyes infousing MemoryDBno
User concepts infoAccess controlnoAccess rights for users and roles on table levelnono

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More resources
BadgerKineticaLovefieldSpark SQL
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