DBMS > AgensGraph vs. Drizzle vs. EsgynDB vs. Postgres-XL

System Properties Comparison AgensGraph vs. Drizzle vs. EsgynDB vs. Postgres-XL

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

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

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Primary database model

Graph DBMS
Relational DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.20
Rank	#321	Overall
	#27	Graph DBMS
	#143	Relational DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Website

bitnine.net/agensgraph

www.esgyn.cn

www.postgres-xl.org

Technical documentation

bitnine.net/documentation

www.postgres-xl.org/documentation

Developer

Bitnine Global Inc.

Drizzle project, originally started by Brian Aker

Esgyn

Initial release

2016

2008

2015

2014

since 2012, originally named StormDB

Current release

2.1, December 2018

7.2.4, September 2012

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

GNU GPL

commercial

Open Source

Mozilla public license

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++

C++, Java

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
OS X

Linux

Linux
macOS

Data scheme

depending on used data model

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.

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

distributed, parallel query execution

APIs and other access methods

Cypher Query Language
JDBC

JDBC

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

C
Java
JavaScript
Python

C
C++
Java
PHP

All languages supporting JDBC/ODBC/ADO.Net

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

yes

Java Stored Procedures

user defined functions

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

Multi-source replication between multi datacenters

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

MVCC

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.

User concepts

Access control

fine grained access rights according to SQL-standard

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

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