DBMS > AgensGraph vs. Drizzle vs. Graph Engine vs. SWC-DB

System Properties Comparison AgensGraph vs. Drizzle vs. Graph Engine vs. SWC-DB

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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.

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

A high performance, scalable Wide Column DBMS

Primary database model

Graph DBMS
Relational DBMS

Relational DBMS

Graph DBMS
Key-value store

Wide column store

Secondary database models

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

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

bitnine.net/agensgraph

www.graphengine.io

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

bitnine.net/documentation

www.graphengine.io/docs/manual

Developer

Bitnine Global Inc.

Drizzle project, originally started by Brian Aker

Microsoft

Alex Kashirin

Initial release

2016

2008

2010

2020

Current release

2.1, December 2018

7.2.4, September 2012

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

GNU GPL

Open Source

MIT License

Open Source

GPL V3

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++

.NET and C

C++

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
OS X

.NET

Linux

Data scheme

depending on used data model

yes

schema-free

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

with proprietary extensions

SQL-like query language

APIs and other access methods

Cypher Query Language
JDBC

JDBC

RESTful HTTP API

Proprietary protocol
Thrift

Supported programming languages

C
Java
JavaScript
Python

C
C++
Java
PHP

C#
C++
F#
Visual Basic

C++

Server-side scripts

Stored procedures

yes

Triggers

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

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