DBMS > Blueflood vs. Drizzle vs. Netezza vs. RisingWave

System Properties Comparison Blueflood vs. Drizzle vs. Netezza vs. RisingWave

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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

Scalable TimeSeries DBMS based on Cassandra

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

Data warehouse and analytics appliance part of IBM PureSystems

A distributed RDBMS for stream processing, wire-compatible with PostgreSQL

Primary database model

Time Series DBMS

Relational DBMS

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

Score	0.06
Rank	#352	Overall
	#36	Time Series DBMS

Score	7.56
Rank	#48	Overall
	#31	Relational DBMS

Score	0.61
Rank	#237	Overall
	#111	Relational DBMS

Website

blueflood.io

www.ibm.com/products/netezza

www.risingwave.com/database

Technical documentation

github.com/rax-maas/blueflood/wiki

docs.risingwave.com/docs/current/intro

Developer

Rackspace

Drizzle project, originally started by Brian Aker

IBM

RisingWave Labs

Initial release

2013

2008

2000

2022

Current release

7.2.4, September 2012

1.2, September 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GNU GPL

commercial

Open Source

Apache Version 2.0

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

Java

C++

Rust

Server operating systems

Linux
OS X

FreeBSD
Linux
OS X

Linux

included in appliance

Docker
Linux
macOS

Data scheme

predefined scheme

yes

Typing

predefined data types such as float or date

yes

Standard SQL-types and JSON

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

yes

APIs and other access methods

HTTP REST

JDBC

JDBC
ODBC
OLE DB

JDBC
PostgreSQL wire protocol

Supported programming languages

C
C++
Java
PHP

C
C++
Fortran
Java
Lua
Perl
Python
R

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

UDFs in Python or Java

Triggers

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

In-memory capabilities

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

yes

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Users with fine-grained authorization concept

Users and Roles

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Recent citations in the news

Real-Time Performance and Health Monitoring Using Netdata
2 September 2019, CNX Software

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21 August 2019, AWS Blog

AWS and IBM Netezza come out in support of Iceberg in table format face-off
1 August 2023, The Register

Copy data from Netezza to Azure with Azure Data Factory
9 September 2019, Microsoft

IBM Completes Acquisition of Netezza
11 November 2010, PR Newswire

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