DBMS > Drizzle vs. Netezza vs. Quasardb vs. SQLite

System Properties Comparison Drizzle vs. Netezza vs. Quasardb vs. SQLite

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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.

Data warehouse and analytics appliance part of IBM PureSystems

Distributed, high-performance timeseries database

Widely used embeddable, in-process RDBMS

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

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

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

www.ibm.com/products/netezza

quasar.ai

www.sqlite.org

Technical documentation

doc.quasar.ai/master

www.sqlite.org/docs.html

Developer

Drizzle project, originally started by Brian Aker

IBM

quasardb

Dwayne Richard Hipp

Initial release

2008

2000

2009

2000

Current release

7.2.4, September 2012

3.14.1, January 2024

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

GNU GPL

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

Public Domain

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

FreeBSD
Linux
OS X

Linux

included in appliance

BSD
Linux
OS X
Windows

server-less

Data scheme

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

integer and binary

yes

not rigid because of 'dynamic typing' concept.

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

with tags

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

SQL-like query language

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC

JDBC
ODBC
OLE DB

HTTP API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C
C++
Java
PHP

C
C++
Fortran
Java
Lua
Perl
Python
R

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

consistent hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

Source-replica replication with selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

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

via file-system locks

Durability

Support for making data persistent

yes

by using LevelDB

yes

In-memory capabilities

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

yes

Transient mode

yes

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Users with fine-grained authorization concept

Cryptographically strong user authentication and audit trail

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