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DBMS > HBase vs. Hive vs. MongoDB

System Properties Comparison HBase vs. Hive vs. MongoDB

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Editorial information provided by DB-Engines
NameHBase  Xexclude from comparisonHive  Xexclude from comparisonMongoDB  Xexclude from comparison
DescriptionWide-column store based on Apache Hadoop and on concepts of BigTabledata warehouse software for querying and managing large distributed datasets, built on HadoopOne of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure
Primary database modelWide column storeRelational DBMSDocument store
Secondary database modelsSpatial DBMS
Search engine infointegrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS infoTime Series Collections introduced in Release 5.0
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score40.04
Rank#26  Overall
#2  Wide column stores
Score77.89
Rank#17  Overall
#11  Relational DBMS
Score469.33
Rank#5  Overall
#1  Document stores
Websitehbase.apache.orghive.apache.orgwww.mongodb.com
Technical documentationhbase.apache.orgcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.mongodb.com/­manual
DeveloperApache Software Foundation infoApache top-level project, originally developed by PowersetApache Software Foundation infoinitially developed by FacebookMongoDB, Inc
Initial release200820122009
Current release2.3.4, January 20213.1.3, April 20226.0.1, August 2022
License infoCommercial or Open SourceOpen Source infoApache version 2Open Source infoApache Version 2Open Source infoMongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.
Cloud-based only infoOnly available as a cloud servicenonono infoMongoDB available as DBaaS (MongoDB Atlas)
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++
Server operating systemsLinux
Unix
Windows infousing Cygwin
All OS with a Java VMLinux
OS X
Solaris
Windows
Data schemeschema-free, schema definition possibleyesschema-free infoAlthough schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.
Typing infopredefined data types such as float or dateoptions to bring your own types, AVROyesyes infostring, integer, double, decimal, boolean, date, object_id, geospatial
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.no
Secondary indexesnoyesyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsRead-only SQL queries via the MongoDB Connector for BI
APIs and other access methodsJava API
RESTful HTTP API
Thrift
JDBC
ODBC
Thrift
proprietary protocol using JSON
Supported programming languagesC
C#
C++
Groovy
Java
PHP
Python
Scala
C++
Java
PHP
Python
Actionscript infounofficial driver
C
C#
C++
Clojure infounofficial driver
ColdFusion infounofficial driver
D infounofficial driver
Dart infounofficial driver
Delphi infounofficial driver
Erlang
Go
Groovy infounofficial driver
Haskell
Java
JavaScript
Lisp infounofficial driver
Lua infounofficial driver
MatLab infounofficial driver
Perl
PHP
PowerShell infounofficial driver
Prolog infounofficial driver
Python
R infounofficial driver
Ruby
Rust
Scala
Smalltalk infounofficial driver
Swift
Server-side scripts infoStored proceduresyes infoCoprocessors in Javayes infouser defined functions and integration of map-reduceJavaScript
Triggersyesnoyes infoin MongoDB Atlas only
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoPartitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
selectable replication factorMulti-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infoquery execution via MapReduceyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyEventual ConsistencyEventual Consistency
Immediate Consistency infocan be individually decided for each write operation
Foreign keys infoReferential integritynonono infotypically not used, however similar functionality with DBRef possible
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataSingle row ACID (across millions of columns)noMulti-document ACID Transactions with snapshot isolation
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes infooptional, enabled by default
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoIn-memory storage engine introduced with MongoDB version 3.2
User concepts infoAccess controlAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAccess rights for users, groups and rolesAccess rights for users and roles

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