DBMS > Amazon DynamoDB vs. Amazon Neptune vs. JaguarDB vs. Kingbase vs. Microsoft Azure Cosmos DB

System Properties Comparison Amazon DynamoDB vs. Amazon Neptune vs. JaguarDB vs. Kingbase vs. Microsoft Azure Cosmos DB

Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

Fast, reliable graph database built for the cloud

Performant, highly scalable DBMS for AI and IoT applications

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

Globally distributed, horizontally scalable, multi-model database service

Primary database model

Document store
Key-value store

Graph DBMS
RDF store

Key-value store
Vector DBMS

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Document store
Spatial DBMS

Spatial DBMS

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

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	2.20
Rank	#119	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	0.45
Rank	#262	Overall
	#123	Relational DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Website

aws.amazon.com/dynamodb

aws.amazon.com/neptune

www.jaguardb.com

www.kingbase.com.cn

azure.microsoft.com/services/cosmos-db

Technical documentation

docs.aws.amazon.com/dynamodb

aws.amazon.com/neptune/developer-resources

www.jaguardb.com/support.html

learn.microsoft.com/azure/cosmos-db

Developer

Amazon

DataJaguar, Inc.

BeiJing KINGBASE Information technologies inc.

Microsoft

Initial release

2012

2017

2015

1999

2014

Current release

3.3 July 2023

V8.0, August 2021

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

GPL V3.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

the server part. Clients available in other languages

C and Java

Server operating systems

hosted

Linux

Linux
Windows

hosted

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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

All properties auto-indexed by default

SQL

Support of SQL

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

Standard with numerous extensions

SQL-like query language

APIs and other access methods

RESTful HTTP API

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

JDBC
ODBC

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

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

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

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Server-side scripts

Stored procedures

user defined functions

JavaScript

Triggers

yes

by integration with AWS Lambda

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Eventual Consistency

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

ACID

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

yes

In-memory capabilities

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

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

rights management via user accounts

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

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