DBMS > Infobright vs. JaguarDB vs. Netezza vs. Riak KV vs. Snowflake

System Properties Comparison Infobright vs. JaguarDB vs. Netezza vs. Riak KV vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Performant, highly scalable DBMS for AI and IoT applications

Data warehouse and analytics appliance part of IBM PureSystems

Distributed, fault tolerant key-value store

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Relational DBMS

Key-value store
Vector DBMS

Relational DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Relational DBMS

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

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

ignitetech.com/softwarelibrary/infobrightdb

www.jaguardb.com

www.ibm.com/products/netezza

www.snowflake.com

Technical documentation

www.jaguardb.com/support.html

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

docs.snowflake.net/manuals/index.html

Developer

Ignite Technologies Inc.; formerly InfoBright Inc.

DataJaguar, Inc.

IBM

OpenSource, formerly Basho Technologies

Snowflake Computing Inc.

Initial release

2005

2015

2000

2009

2014

Current release

3.3 July 2023

3.2.0, December 2022

License

Commercial or Open Source

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

GPL V3.0

commercial

Open Source

Apache version 2, commercial enterprise edition

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

the server part. Clients available in other languages

Erlang

Server operating systems

Linux
Windows

Linux

included in appliance

Linux
OS X

hosted

Data scheme

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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.

yes

Secondary indexes

Knowledge Grid Technology used instead

yes

restricted

SQL

Support of SQL

yes

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

JDBC
ODBC

JDBC
ODBC
OLE DB

HTTP API
Native Erlang Interface

CLI Client
JDBC
ODBC

Supported programming languages

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

C
C++
Fortran
Java
Lua
Perl
Python
R

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Erlang

user defined functions

Triggers

yes

pre-commit hooks and post-commit hooks

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

no "single point of failure"

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

Source-replica replication

selectable replication factor

yes

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

Immediate Consistency

Foreign keys

Referential integrity

links between data sets can be stored

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

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

rights management via user accounts

Users with fine-grained authorization concept

yes, using Riak Security

Users with fine-grained authorization concept, user roles and pluggable authentication

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