DBMS > Amazon Redshift vs. EsgynDB vs. Geode vs. openGemini vs. Percona Server for MongoDB

System Properties Comparison Amazon Redshift vs. EsgynDB vs. Geode vs. openGemini vs. Percona Server for MongoDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

An open source distributed Time Series DBMS with high concurrency, high performance, and high scalability

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

Primary database model

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	1.92
Rank	#131	Overall
	#23	Key-value stores

Score	0.01
Rank	#375	Overall
	#39	Time Series DBMS

Score	0.52
Rank	#254	Overall
	#39	Document stores

Website

aws.amazon.com/redshift

www.esgyn.cn

geode.apache.org

www.opengemini.org
github.com/openGemini

www.percona.com/mongodb/software/percona-server-for-mongodb

Technical documentation

docs.aws.amazon.com/redshift

geode.apache.org/docs

docs.opengemini.org/guide

docs.percona.com/percona-distribution-for-mongodb

Developer

Amazon (based on PostgreSQL)

Esgyn

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Huawei and openGemini community

Percona

Initial release

2012

2015

2002

2022

2015

Current release

1.1, February 2017

1.1, July 2023

3.4.10-2.10, November 2017

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

Apache Version 2.0

Open Source

GPL Version 2

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

Java

C++

Server operating systems

hosted

Linux

All OS with a Java VM

the JDK (8 or later) is also required

Linux
Windows

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Integer, Float, Boolean, String

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

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

SQL-like query language (OQL)

SQL-like query language

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC

Java Client API
Memcached protocol
RESTful HTTP API

HTTP REST

proprietary protocol using JSON

Supported programming languages

All languages supporting JDBC/ODBC

All languages supporting JDBC/ODBC/ADO.Net

.Net
All JVM based languages
C++
Groovy
Java
Scala

C
C++
Go
Java
JavaScript (Node.js)
Python
Rust

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

Server-side scripts

Stored procedures

user defined functions

in Python

Java Stored Procedures

user defined functions

JavaScript

Triggers

yes

Cache Event Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication between multi datacenters

Multi-source replication

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

yes, on a single node

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.

yes

via In-Memory Engine

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights per client and object definable

Administrators and common users accounts

Access rights for users and roles

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