DBMS > EsgynDB vs. Graph Engine vs. STSdb

System Properties Comparison EsgynDB vs. Graph Engine vs. STSdb

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Editorial information provided by DB-Engines

Name

Description

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

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Key-value store

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

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

www.esgyn.cn

www.graphengine.io

github.com/STSSoft/STSdb4

Technical documentation

www.graphengine.io/docs/manual

Developer

Esgyn

Microsoft

STS Soft SC

Initial release

2015

2010

2011

Current release

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open Source

MIT License

Open Source

GPLv2, commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++, Java

.NET and C

Server operating systems

Linux

.NET

Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

SQL

Support of SQL

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

RESTful HTTP API

.NET Client API

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

C#
C++
F#
Visual Basic

C#
Java

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

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More resources

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provided by Google News

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