DBMS > Amazon Redshift vs. EsgynDB vs. Sequoiadb

System Properties Comparison Amazon Redshift vs. EsgynDB vs. Sequoiadb

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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

NewSQL database with distributed OLTP and SQL

Primary database model

Relational DBMS

Document store
Relational DBMS

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

Score	14.21
Rank	#38	Overall
	#23	Relational DBMS

Score	0.16
Rank	#324	Overall
	#145	Relational DBMS

Score	0.39
Rank	#265	Overall
	#41	Document stores
	#123	Relational DBMS

Website

aws.amazon.com/redshift

www.esgyn.cn

www.sequoiadb.com

Technical documentation

docs.aws.amazon.com/redshift

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Amazon (based on PostgreSQL)

Esgyn

Sequoiadb Ltd.

Initial release

2012

2015

2013

License

Commercial or Open Source

commercial

Open Source

Server: AGPL; Client: Apache V2

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

C++

Server operating systems

hosted

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC

proprietary protocol using JSON

Supported programming languages

All languages supporting JDBC/ODBC

All languages supporting JDBC/ODBC/ADO.Net

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in Python

Java Stored Procedures

JavaScript

Triggers

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

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

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

Document is locked during a transaction

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

User concepts

Access control

fine grained access rights according to SQL-standard

simple password-based access control

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