DBMS > Amazon DocumentDB vs. MySQL vs. openGauss vs. TigerGraph vs. Trafodion

System Properties Comparison Amazon DocumentDB vs. MySQL vs. openGauss vs. TigerGraph 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

An enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by Huawei

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Transactional SQL-on-Hadoop DBMS

Primary database model

Document store

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Graph DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	1.91
Rank	#131	Overall
	#24	Document stores

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	1.06
Rank	#184	Overall
	#84	Relational DBMS

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Website

aws.amazon.com/documentdb

www.mysql.com

gitee.com/opengauss
opengauss.org

www.tigergraph.com

trafodion.apache.org

Technical documentation

aws.amazon.com/documentdb/resources

dev.mysql.com/doc

docs.opengauss.org/en
gitee.com/opengauss/docs

docs.tigergraph.com

trafodion.apache.org/documentation.html

Developer

Oracle

since 2010, originally MySQL AB, then Sun

Huawei and openGauss community

Apache Software Foundation, originally developed by HP

Initial release

2019

1995

2019

2017

2014

Current release

8.4.0, April 2024

3.0, March 2022

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

commercial

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

C++

C++, Java

Server operating systems

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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

ANSI SQL 2011

SQL-like query language (GSQL)

yes

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

ADO.NET
JDBC
ODBC
Proprietary native API

JDBC
ODBC

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON 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

C
C++
Java

C++
Java

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

yes

proprietary syntax

yes

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

horizontal partitioning (by range, list and hash)

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, 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

Relationships in graphs

yes

Transaction concepts

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

Atomic single-document operations

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

Access rights for users, groups and roles according to SQL-standard

Role-based access control

fine grained access rights according to SQL-standard

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