DBMS > Amazon DocumentDB vs. MySQL vs. RethinkDB vs. SiriDB vs. Trafodion

System Properties Comparison Amazon DocumentDB vs. MySQL vs. RethinkDB vs. SiriDB vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Widely used open source RDBMS

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Open Source Time Series DBMS

Transactional SQL-on-Hadoop DBMS

Primary database model

Document store

Relational DBMS

Key/Value like access via memcached API

Document store

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Spatial DBMS

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

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	2.74
Rank	#105	Overall
	#19	Document stores

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

aws.amazon.com/documentdb

Technical documentation

aws.amazon.com/documentdb/resources

dev.mysql.com/doc

rethinkdb.com/docs

docs.siridb.com

trafodion.apache.org/documentation.html

Developer

Oracle

since 2010, originally MySQL AB, then Sun

The Linux Foundation

since July 2017

Cesbit

Apache Software Foundation, originally developed by HP

Initial release

2019

1995

2009

2017

2014

Current release

8.4.0, April 2024

2.4.1, August 2020

2.3.0, February 2019

License

Commercial or Open Source

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache Version 2

Open Source

MIT License

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C and C++

C++

C++, Java

Server operating systems

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Linux

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

yes

Numeric data

yes

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

SQL

Support of SQL

yes

with proprietary extensions

yes

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP API

ADO.NET
JDBC
ODBC

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

yes

proprietary syntax

Java Stored Procedures

Triggers

yes

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

range based

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication
Source-replica replication

Source-replica replication

yes

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

not for MyISAM storage engine

yes

Transaction concepts

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

Atomic single-document operations

ACID

not for MyISAM storage engine

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

MVCC based

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users and roles

Users with fine-grained authorization concept

no user groups or roles

yes

users and table-level permissions

simple rights management via user accounts

fine grained access rights according to SQL-standard

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