DBMS > EsgynDB vs. etcd vs. Graph Engine vs. Transwarp StellarDB

System Properties Comparison EsgynDB vs. etcd vs. Graph Engine vs. Transwarp StellarDB

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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

A distributed graph DBMS built for enterprise-level graph applications

Primary database model

Relational DBMS

Key-value store

Graph DBMS
Key-value store

Graph DBMS

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

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	7.05
Rank	#53	Overall
	#5	Key-value stores

Score	0.56
Rank	#241	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	0.00
Rank	#385	Overall
	#40	Graph DBMS

Website

www.esgyn.cn

etcd.io
github.com/etcd-io/etcd

www.graphengine.io

www.transwarp.cn/en/product/stellardb

Technical documentation

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

www.graphengine.io/docs/manual

Developer

Esgyn

Microsoft

Transwarp

Initial release

2015

2010

Current release

3.4, August 2019

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

MIT License

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++, Java

.NET and C

Server operating systems

Linux

FreeBSD
Linux
Windows

experimental

.NET

Data scheme

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

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

ADO.NET
JDBC
ODBC

gRPC
JSON over HTTP

RESTful HTTP API

OpenCypher

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

C#
C++
F#
Visual Basic

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Triggers

yes, watching key changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

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

yes

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