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DBMS > Amazon DocumentDB vs. Atos Standard Common Repository vs. HBase vs. Hive

System Properties Comparison Amazon DocumentDB vs. Atos Standard Common Repository vs. HBase vs. Hive

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonHBase  Xexclude from comparisonHive  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksWide-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 modelDocument storeDocument store
Key-value store
Wide column storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score27.97
Rank#26  Overall
#2  Wide column stores
Score59.76
Rank#18  Overall
#12  Relational DBMS
Websiteaws.amazon.com/­documentdbatos.net/en/convergence-creators/portfolio/standard-common-repositoryhbase.apache.orghive.apache.org
Technical documentationaws.amazon.com/­documentdb/­resourceshbase.apache.org/­book.htmlcwiki.apache.org/­confluence/­display/­Hive/­Home
DeveloperAtos Convergence CreatorsApache Software Foundation infoApache top-level project, originally developed by PowersetApache Software Foundation infoinitially developed by Facebook
Initial release2019201620082012
Current release17032.3.4, January 20213.1.3, April 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache version 2Open Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJava
Server operating systemshostedLinuxLinux
Unix
Windows infousing Cygwin
All OS with a Java VM
Data schemeschema-freeSchema and schema-less with LDAP viewsschema-free, schema definition possibleyes
Typing infopredefined data types such as float or dateyesoptionaloptions 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.noyesno
Secondary indexesyesyesnoyes
SQL infoSupport of SQLnononoSQL-like DML and DDL statements
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)LDAPJava API
RESTful HTTP API
Thrift
JDBC
ODBC
Thrift
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
All languages with LDAP bindingsC
C#
C++
Groovy
Java
PHP
Python
Scala
C++
Java
PHP
Python
Server-side scripts infoStored proceduresnonoyes infoCoprocessors in Javayes infouser defined functions and integration of map-reduce
Triggersnoyesyesno
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infocell divisionShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyesMulti-source replication
Source-replica replication
selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yesyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency or Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsAtomic execution of specific operationsSingle 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.yesyes
User concepts infoAccess controlAccess rights for users and rolesLDAP bind authenticationAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAccess rights for users, groups and roles

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More resources
Amazon DocumentDBAtos Standard Common RepositoryHBaseHive
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