DBMS > Amazon DocumentDB vs. HugeGraph vs. MySQL vs. TerminusDB vs. TypeDB

System Properties Comparison Amazon DocumentDB vs. HugeGraph vs. MySQL vs. TerminusDB vs. TypeDB

Editorial information provided by DB-Engines

Name

Description

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

A fast-speed and highly-scalable Graph DBMS

Widely used open source RDBMS

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

TypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language

Primary database model

Document store

Graph DBMS

Relational DBMS

Key/Value like access via memcached API

Graph DBMS

Graph DBMS
Relational DBMS

Often described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.

Secondary database models

Document store
Spatial DBMS

Document store
RDF store

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

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Score	0.65
Rank	#234	Overall
	#20	Graph DBMS
	#107	Relational DBMS

Website

aws.amazon.com/documentdb

github.com/hugegraph
hugegraph.apache.org

www.mysql.com

terminusdb.com

typedb.com

Technical documentation

aws.amazon.com/documentdb/resources

hugegraph.apache.org/docs

dev.mysql.com/doc

terminusdb.github.io/terminusdb/#

typedb.com/docs

Developer

Baidu

Oracle

since 2010, originally MySQL AB, then Sun

DataChemist Ltd.

Vaticle

Initial release

2019

2018

1995

2018

2016

Current release

0.9

8.4.0, April 2024

11.0.0, January 2023

2.26.3, January 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

GPL V3

Open Source

GPL Version 3, commercial licenses available

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C and C++

Prolog, Rust

Java

Server operating systems

hosted

Linux
macOS
Unix

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Linux
OS X
Windows

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

also supports composite index and range index

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-like query language (WOQL)

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

Java API
RESTful HTTP API
TinkerPop Gremlin

ADO.NET
JDBC
ODBC
Proprietary native API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

Groovy
Java
Python

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

JavaScript
Python

All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

yes

proprietary syntax

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

depending on used storage backend, e.g. Cassandra and HBase

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Graph Partitioning

Sharding

by using Cassandra

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

depending on used storage backend, e.g. Cassandra and HBase

Multi-source replication
Source-replica replication

Journaling Streams

Multi-source replication

by using Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

via hugegraph-spark

yes

by using Apache Kafka and Apache Zookeeper

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

edges in graph

yes

not for MyISAM storage engine

yes

substituted by the relationship feature

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 journaling

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, roles and permissions

Users with fine-grained authorization concept

no user groups or roles

Role-based access control

yes

at REST API level; other APIs in progress

More information provided by the system vendor

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Licensing and pricing models

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