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DBMS > Badger vs. eXtremeDB vs. HBase vs. Hive

System Properties Comparison Badger vs. eXtremeDB vs. HBase vs. Hive

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisoneXtremeDB  Xexclude from comparisonHBase  Xexclude from comparisonHive  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Natively in-memory DBMS with options for persistency, high-availability and clusteringWide-column store based on Apache Hadoop and on concepts of BigTabledata warehouse software for querying and managing large distributed datasets, built on Hadoop
Primary database modelKey-value storeRelational DBMS
Time Series DBMS
Wide column storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#320  Overall
#47  Key-value stores
Score0.80
Rank#214  Overall
#99  Relational DBMS
#18  Time Series DBMS
Score27.97
Rank#26  Overall
#2  Wide column stores
Score59.76
Rank#18  Overall
#12  Relational DBMS
Websitegithub.com/­dgraph-io/­badgerwww.mcobject.comhbase.apache.orghive.apache.org
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerwww.mcobject.com/­docs/­extremedb.htmhbase.apache.org/­book.htmlcwiki.apache.org/­confluence/­display/­Hive/­Home
DeveloperDGraph LabsMcObjectApache Software Foundation infoApache top-level project, originally developed by PowersetApache Software Foundation infoinitially developed by Facebook
Initial release2017200120082012
Current release8.2, 20212.3.4, January 20213.1.3, April 2022
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoApache version 2Open Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoC and C++JavaJava
Server operating systemsBSD
Linux
OS X
Solaris
Windows
AIX
HP-UX
Linux
macOS
Solaris
Windows
Linux
Unix
Windows infousing Cygwin
All OS with a Java VM
Data schemeschema-freeyesschema-free, schema definition possibleyes
Typing infopredefined data types such as float or datenoyesoptions to bring your own types, AVROyes
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.nono infosupport of XML interfaces availableno
Secondary indexesnoyesnoyes
SQL infoSupport of SQLnoyes infowith the option: eXtremeSQLnoSQL-like DML and DDL statements
APIs and other access methods.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
JDBC
ODBC
Thrift
Supported programming languagesGo.Net
C
C#
C++
Java
Lua
Python
Scala
C
C#
C++
Groovy
Java
PHP
Python
Scala
C++
Java
PHP
Python
Server-side scripts infoStored proceduresnoyesyes infoCoprocessors in Javayes infouser defined functions and integration of map-reduce
Triggersnoyes infoby defining eventsyesno
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning / shardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneActive Replication Fabricâ„¢ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
Multi-source replication
Source-replica replication
selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate Consistency or Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDSingle row ACID (across millions of columns)no
Concurrency infoSupport for concurrent manipulation of datayesyes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyes
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.noyesyes
User concepts infoAccess controlnoAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAccess rights for users, groups and roles
More information provided by the system vendor
BadgereXtremeDBHBaseHive
Specific characteristicseXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
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Competitive advantageseXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
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Typical application scenariosIoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more
Key customersSchneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more
Market metricsWith hundreds of customers and over 30 million devices/applications using the product...
» more
Licensing and pricing modelsFor server use cases, there is a simple per-server license irrespective of the number...
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BadgereXtremeDBHBaseHive
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