DBMS > Amazon DynamoDB vs. EsgynDB vs. Faircom EDGE vs. MaxDB vs. PouchDB

System Properties Comparison Amazon DynamoDB vs. EsgynDB vs. Faircom EDGE vs. MaxDB vs. PouchDB

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

FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments

A robust and reliable RDBMS optimized to run all major SAP solutions

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Document store
Key-value store

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

Document store

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	0.02
Rank	#368	Overall
	#54	Key-value stores
	#156	Relational DBMS

Score	2.32
Rank	#112	Overall
	#55	Relational DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Website

aws.amazon.com/dynamodb

www.esgyn.cn

www.faircom.com/products/faircom-edge

maxdb.sap.com

pouchdb.com

Technical documentation

docs.aws.amazon.com/dynamodb

docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html

maxdb.sap.com/documentation

pouchdb.com/guides

Developer

Amazon

Esgyn

FairCom Corporation

SAP, acquired from Software AG (Adabas-D) in 1997

Apache Software Foundation

Initial release

2012

2015

1979

1984

2012

Current release

V3, October 2020

7.9.10.12, February 2024

7.1.1, June 2019

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Restricted, free version available

commercial

Limited community edition free

Open Source

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++, Java

ANSI C, C++

C++

JavaScript

Server operating systems

hosted

Linux

Android
Linux

ARM, x86
Raspbian
Windows

AIX
HP-UX
Linux
Solaris
Windows

server-less, requires a JavaScript environment (browser, Node.js)

Data scheme

schema-free

yes

Flexible Schema (defined schema, partial schema, schema free)

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

via views

SQL

Support of SQL

yes

ANSI SQL queries

yes

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
ODBC

ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
WebDAV

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

All languages supporting JDBC/ODBC/ADO.Net

C
C#
C++
Java
JavaScript
PHP
Python
VB.Net

.Net
C#
Java
Perl
PHP
Python

JavaScript

Server-side scripts

Stored procedures

Java Stored Procedures

yes

.Net, JavaScript, C/C++

yes

View functions in JavaScript

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

File partitioning

Customizable business rules for partitioning

none

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication between multi datacenters

yes

Synchronous and asynchronous realtime replication based on transaction logs

Source-replica replication

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

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

Immediate Consistency
Tunable Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

when using SQL

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

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

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)

fine grained access rights according to SQL-standard

Fine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

fine grained access rights according to SQL-standard

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