DBMS > Amazon Neptune vs. Kyligence Enterprise vs. MySQL vs. OrigoDB vs. TerminusDB

System Properties Comparison Amazon Neptune vs. Kyligence Enterprise vs. MySQL vs. OrigoDB vs. TerminusDB

Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

A distributed analytics engine for big data, built on top of Apache Kylin

Widely used open source RDBMS

A fully ACID in-memory object graph database

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

Primary database model

Graph DBMS
RDF store

Relational DBMS

Key/Value like access via memcached API

Document store
Object oriented DBMS

Graph DBMS

Secondary database models

Document store
Spatial DBMS

Document store
RDF store

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

Score	2.29
Rank	#113	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	0.46
Rank	#266	Overall
	#124	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Website

aws.amazon.com/neptune

kyligence.io/kyligence-enterprise

www.mysql.com

origodb.com

terminusdb.com

Technical documentation

aws.amazon.com/neptune/developer-resources

dev.mysql.com/doc

origodb.com/docs

terminusdb.github.io/terminusdb/#

Developer

Amazon

Kyligence, Inc.

Oracle

since 2010, originally MySQL AB, then Sun

Robert Friberg et al

DataChemist Ltd.

Initial release

2017

2016

1995

2009

under the name LiveDB

2018

Current release

8.4.0, April 2024

11.0.0, January 2023

License

Commercial or Open Source

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C and C++

Prolog, Rust

Server operating systems

hosted

Linux

FreeBSD
Linux
OS X
Solaris
Windows

Linux
Windows

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

yes

with proprietary extensions

SQL-like query language (WOQL)

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

.NET Client API
HTTP API
LINQ

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

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

.Net

JavaScript
Python

Server-side scripts

Stored procedures

yes

proprietary syntax

yes

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

horizontal partitioning

client side managed; servers are not synchronized

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.

Multi-source replication
Source-replica replication

Source-replica replication

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

not for MyISAM storage engine

depending on model

yes

Transaction concepts

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

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

with encyption-at-rest

yes

Write ahead log

yes

in-memory journaling

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 can be defined via the AWS Identity and Access Management (IAM)

Users with fine-grained authorization concept

no user groups or roles

Role based authorization

Role-based access control

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