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

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

Editorial information provided by DB-Engines

Name

Description

Performant, highly scalable DBMS for AI and IoT applications

Data warehouse and analytics appliance part of IBM PureSystems

NuoDB is a webscale distributed database that supports SQL and ACID transactions

Distributed, fault tolerant key-value store

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

Primary database model

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

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

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

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

www.jaguardb.com

www.ibm.com/products/netezza

www.3ds.com/nuodb-distributed-sql-database

www.snowflake.com

Technical documentation

www.jaguardb.com/support.html

doc.nuodb.com

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

docs.snowflake.net/manuals/index.html

Developer

DataJaguar, Inc.

IBM

Dassault Systèmes

originally NuoDB, Inc.

OpenSource, formerly Basho Technologies

Snowflake Computing Inc.

Initial release

2015

2000

2013

2009

2014

Current release

3.3 July 2023

3.2.0, December 2022

License

Commercial or Open Source

Open Source

GPL V3.0

commercial

limited edition free

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

C++

Erlang

Server operating systems

Linux

included in appliance

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

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

yes

restricted

SQL

Support of SQL

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

APIs and other access methods

JDBC
ODBC

JDBC
ODBC
OLE DB

ADO.NET
JDBC
ODBC

HTTP API
Native Erlang Interface

CLI Client
JDBC
ODBC

Supported programming languages

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

C
C++
Fortran
Java
Lua
Perl
Python
R

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

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

Java, SQL

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

Sharding

data is dynamically stored/cached on the nodes where it is read/written

Sharding

no "single point of failure"

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

yes

Managed transparently by NuoDB

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

Eventual Consistency

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

yes

Transaction concepts

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

ACID

tunable commit protocol

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

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

Temporary table

User concepts

Access control

rights management via user accounts

Users with fine-grained authorization concept

Standard SQL roles/ privileges, Administrative Users

yes, using Riak Security

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

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