DBMS > Altibase vs. Dolt vs. Drizzle vs. Sequoiadb

System Properties Comparison Altibase vs. Dolt vs. Drizzle vs. Sequoiadb

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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

An enterprise grade, high-performance RDBMS

A MySQL compatible DBMS with Git-like versioning of data and schema

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

NewSQL database with distributed OLTP and SQL

Primary database model

Relational DBMS

Document store
Relational DBMS

Secondary database models

Document store

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

Score	1.07
Rank	#186	Overall
	#87	Relational DBMS

Score	0.96
Rank	#193	Overall
	#90	Relational DBMS

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Website

altibase.com

github.com/dolthub/dolt
www.dolthub.com

www.sequoiadb.com

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

docs.dolthub.com

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Altibase

DoltHub Inc

Drizzle project, originally started by Brian Aker

Sequoiadb Ltd.

Initial release

1999

2018

2008

2013

Current release

v7.3, 2023, August 2023

7.2.4, September 2012

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

Open Source

Apache Version 2.0

Open Source

GNU GPL

Open Source

Server: AGPL; Client: Apache V2

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++

Server operating systems

AIX
HP-UX
Linux

Linux
macOS
Windows

FreeBSD
Linux
OS X

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

ANSI SQL-92

yes

with proprietary extensions

SQL-like query language

APIs and other access methods

JDBC
ODBC
Proprietary protocol

CLI Client
HTTP REST

JDBC

proprietary protocol using JSON

Supported programming languages

C
C++
Java

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
C++
Java
PHP

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

stored procedures and stored functions

yes

currently in alpha release

JavaScript

Triggers

yes

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

A database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.

Multi-source replication
Source-replica 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

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Document is locked during a transaction

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Only one user is configurable, and must be specified in the config file at startup

Pluggable authentication mechanisms

e.g. LDAP, HTTP

simple password-based access control

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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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