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DBMS > Badger vs. Hive vs. SiteWhere vs. Spark SQL

System Properties Comparison Badger vs. Hive vs. SiteWhere vs. Spark SQL

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonHive  Xexclude from comparisonSiteWhere  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.data warehouse software for querying and managing large distributed datasets, built on HadoopM2M integration platform for persisting/querying time series dataSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeRelational DBMSTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#320  Overall
#47  Key-value stores
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score0.06
Rank#383  Overall
#43  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­dgraph-io/­badgerhive.apache.orggithub.com/­sitewhere/­sitewherespark.apache.org/­sql
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgercwiki.apache.org/­confluence/­display/­Hive/­Homesitewhere1.sitewhere.io/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDGraph LabsApache Software Foundation infoinitially developed by FacebookSiteWhereApache Software Foundation
Initial release2017201220102014
Current release3.1.3, April 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2Open Source infoCommon Public Attribution License Version 1.0Open 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 languageGoJavaJavaScala
Server operating systemsBSD
Linux
OS X
Solaris
Windows
All OS with a Java VMLinux
OS X
Windows
Linux
OS X
Windows
Data schemeschema-freeyespredefined schemeyes
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.nonono
Secondary indexesnoyesnono
SQL infoSupport of SQLnoSQL-like DML and DDL statementsnoSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
Thrift
HTTP RESTJDBC
ODBC
Supported programming languagesGoC++
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceno
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infobased on HBaseyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication factorselectable replication factor infobased on HBasenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononono
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 controlnoAccess rights for users, groups and rolesUsers with fine-grained authorization conceptno

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More resources
BadgerHiveSiteWhereSpark SQL
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