DBMS > Amazon DocumentDB vs. Atos Standard Common Repository vs. HBase vs. MongoDB vs. Riak KV

System Properties Comparison Amazon DocumentDB vs. Atos Standard Common Repository vs. HBase vs. MongoDB vs. Riak KV

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

Wide-column store based on Apache Hadoop and on concepts of BigTable

One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure

Distributed, fault tolerant key-value store

Primary database model

Document store

Document store
Key-value store

Wide column store

Document store

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Secondary database models

Spatial DBMS
Search engine

integrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS

Time Series Collections introduced in Release 5.0
Vector DBMS

currently available in the MongoDB Atlas cloud service only

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	421.65
Rank	#5	Overall
	#1	Document stores

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Website

aws.amazon.com/documentdb

atos.net/en/convergence-creators/portfolio/standard-common-repository

hbase.apache.org

www.mongodb.com

Technical documentation

aws.amazon.com/documentdb/resources

hbase.apache.org/book.html

www.mongodb.com/docs/manual

www.tiot.jp/riak-docs/riak/kv/latest

Developer

Atos Convergence Creators

Apache Software Foundation

Apache top-level project, originally developed by Powerset

MongoDB, Inc

OpenSource, formerly Basho Technologies

Initial release

2019

2016

2008

2009

Current release

1703

2.3.4, January 2021

6.0.7, June 2023

3.2.0, December 2022

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.

Open Source

Apache version 2, commercial enterprise edition

Cloud-based only

Only available as a cloud service

yes

MongoDB available as DBaaS (MongoDB Atlas)

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Implementation language

Java

C++

Erlang

Server operating systems

hosted

Linux

Linux
Unix
Windows

using Cygwin

Linux
OS X
Solaris
Windows

Linux
OS X

Data scheme

schema-free

Schema and schema-less with LDAP views

schema-free, schema definition possible

schema-free

Although 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.

schema-free

Typing

predefined data types such as float or date

yes

optional

options to bring your own types, AVRO

yes

string, integer, double, decimal, boolean, date, object_id, geospatial

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

restricted

SQL

Support of SQL

Read-only SQL queries via the MongoDB Atlas SQL Interface

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

LDAP

Java API
RESTful HTTP API
Thrift

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

HTTP API
Native Erlang Interface

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

All languages with LDAP bindings

C
C#
C++
Groovy
Java
PHP
Python
Scala

Actionscript

unofficial driver
C
C#
C++
Clojure

unofficial driver
ColdFusion

unofficial driver
D

unofficial driver
Dart

unofficial driver
Delphi

unofficial driver
Erlang
Go
Groovy

unofficial driver
Haskell
Java
JavaScript
Kotlin
Lisp

unofficial driver
Lua

unofficial driver
MatLab

unofficial driver
Perl
PHP
PowerShell

unofficial driver
Prolog

unofficial driver
Python
R

unofficial driver
Ruby
Rust
Scala
Smalltalk

unofficial driver
Swift

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

yes

Coprocessors in Java

JavaScript

Erlang

Triggers

yes

in MongoDB Atlas only

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

cell division

Sharding

Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

yes

Multi-source replication
Source-replica replication

Multi-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency or Eventual Consistency

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Eventual Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

links between data sets can be stored

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Atomic single-document operations

Atomic execution of specific operations

Single row ACID (across millions of columns)

Multi-document ACID Transactions with snapshot isolation

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional, enabled by default

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

In-memory storage engine introduced with MongoDB version 3.2

User concepts

Access control

Access rights for users and roles

LDAP bind authentication

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

Access rights for users and roles

yes, using Riak Security

More information provided by the system vendor

Specific characteristics

MongoDB provides an integrated suite of cloud database and data services to accelerate...
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Competitive advantages

Built around the flexible document data model and unified API, MongoDB is a developer...
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Typical application scenarios

AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
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Key customers

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
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Market metrics

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
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Licensing and pricing models

MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
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