DBMS > Drizzle vs. EventStoreDB vs. openGauss vs. Riak TS

System Properties Comparison Drizzle vs. EventStoreDB vs. openGauss vs. Riak TS

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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

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

Industrial-strength, open-source database solution built from the ground up for event sourcing.

An enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by Huawei

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	1.19
Rank	#173	Overall
	#1	Event Stores

Score	1.06
Rank	#184	Overall
	#84	Relational DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Website

www.eventstore.com

gitee.com/opengauss
opengauss.org

Technical documentation

developers.eventstore.com

docs.opengauss.org/en
gitee.com/opengauss/docs

www.tiot.jp/riak-docs/riak/ts/latest

Developer

Drizzle project, originally started by Brian Aker

Event Store Limited

Huawei and openGauss community

Open Source, formerly Basho Technologies

Initial release

2008

2012

2019

2015

Current release

7.2.4, September 2012

21.2, February 2021

3.0, March 2022

3.0.0, September 2022

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

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, C++, Java

Erlang

Server operating systems

FreeBSD
Linux
OS X

Linux
Windows

Linux

Linux
OS X

Data scheme

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

restricted

SQL

Support of SQL

yes

with proprietary extensions

ANSI SQL 2011

yes, limited

APIs and other access methods

JDBC

JDBC
ODBC

HTTP API
Native Erlang Interface

Supported programming languages

C
C++
Java
PHP

C
C++
Java

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

yes

Erlang

Triggers

hooks for callbacks inside the server can be used.

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by range, list and hash)

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

selectable replication factor

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

links between datasets can be stored

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

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights for users, groups and roles according to SQL-standard

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More resources

DB-Engines blog posts

MySQL won the April ranking; did its forks follow?
1 April 2015, Paul Andlinger

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1 July 2013, Matthias Gelbmann

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