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DBMS > Badger vs. GeoMesa vs. HBase vs. Spark SQL

System Properties Comparison Badger vs. GeoMesa vs. HBase vs. Spark SQL

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonGeoMesa  Xexclude from comparisonHBase  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.Wide-column store based on Apache Hadoop and on concepts of BigTableSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeSpatial DBMSWide column storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score0.78
Rank#213  Overall
#4  Spatial DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­dgraph-io/­badgerwww.geomesa.orghbase.apache.orgspark.apache.org/­sql
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerwww.geomesa.org/­documentation/­stable/­user/­index.htmlhbase.apache.org/­book.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDGraph LabsCCRi and othersApache Software Foundation infoApache top-level project, originally developed by PowersetApache Software Foundation
Initial release2017201420082014
Current release4.0.5, February 20242.3.4, January 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache License 2.0Open Source infoApache version 2Open 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 languageGoScalaJavaScala
Server operating systemsBSD
Linux
OS X
Solaris
Windows
Linux
Unix
Windows infousing Cygwin
Linux
OS X
Windows
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.nononono
Secondary indexesnoyesnono
SQL infoSupport of SQLnononoSQL-like DML and DDL statements
APIs and other access methodsJava API
RESTful HTTP API
Thrift
JDBC
ODBC
Supported programming languagesGoC
C#
C++
Groovy
Java
PHP
Python
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonoyes infoCoprocessors in Javano
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesnonedepending on storage layerShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnonedepending on storage layerMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemnonedepending on storage layerImmediate Consistency or Eventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoSingle row ACID (across millions of columns)no
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.nodepending on storage layeryesno
User concepts infoAccess controlnoyes infodepending on the DBMS used for storageAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACno

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More resources
BadgerGeoMesaHBaseSpark SQL
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