DBMS > Amazon DynamoDB vs. EsgynDB vs. mSQL vs. Riak KV vs. StarRocks

System Properties Comparison Amazon DynamoDB vs. EsgynDB vs. mSQL vs. Riak KV vs. StarRocks

Editorial information provided by DB-Engines

Name

Description

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

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

mSQL (Mini SQL) is a simple and lightweight RDBMS

Distributed, fault tolerant key-value store

An open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics

Forked from Apache Doris

Primary database model

Document store
Key-value store

Relational DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Relational 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	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	1.04
Rank	#189	Overall
	#88	Relational DBMS

Website

aws.amazon.com/dynamodb

www.esgyn.cn

hughestech.com.au/products/msql

www.starrocks.io

Technical documentation

docs.aws.amazon.com/dynamodb

www.tiot.jp/riak-docs/riak/kv/latest

docs.starrocks.io/en-us/latest/introduction/StarRocks_intro

Developer

Amazon

Esgyn

Hughes Technologies

OpenSource, formerly Basho Technologies

The Linux Foundation

since Feb 2023

Initial release

2012

2015

1994

2009

2020

Current release

4.4, October 2021

3.2.0, December 2022

2.5.3, March 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

free licenses can be provided

Open Source

Apache version 2, commercial enterprise edition

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++, Java

Erlang

C++, Java

Server operating systems

hosted

Linux

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
OS X

Linux

Data scheme

schema-free

yes

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.

Secondary indexes

yes

restricted

yes

SQL

Support of SQL

yes

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
ODBC

JDBC
ODBC

HTTP API
Native Erlang Interface

JDBC
MySQL protocol

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

All languages supporting JDBC/ODBC/ADO.Net

C
C++
Delphi
Java
Perl
PHP
Tcl

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Java

Server-side scripts

Stored procedures

Java Stored Procedures

Erlang

user defined functions

Triggers

yes

by integration with AWS Lambda

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

no "single point of failure"

horizontal partitioning (by range and hash)

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication between multi datacenters

none

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

none

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

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

Concurrency

Support for concurrent manipulation of data

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.

User concepts

Access control

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

fine grained access rights according to SQL-standard

yes, using Riak Security

Role based access control and fine grained access rights

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