DBMS > Derby vs. IBM Cloudant vs. Kinetica vs. Netezza vs. Snowflake

System Properties Comparison Derby vs. IBM Cloudant vs. Kinetica vs. Netezza vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Database as a Service offering based on Apache CouchDB

Fully vectorized database across both GPUs and CPUs

Data warehouse and analytics appliance part of IBM PureSystems

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

Primary database model

Relational DBMS

Document store

Relational DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	4.71
Rank	#69	Overall
	#37	Relational DBMS

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

db.apache.org/derby

www.ibm.com/products/cloudant

www.kinetica.com

www.ibm.com/products/netezza

www.snowflake.com

Technical documentation

db.apache.org/derby/manuals/index.html

cloud.ibm.com/docs/Cloudant

docs.kinetica.com

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Kinetica

IBM

Snowflake Computing Inc.

Initial release

1997

2010

2012

2000

2014

Current release

10.17.1.0, November 2023

7.1, August 2021

License

Commercial or Open Source

Open Source

Apache version 2

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

Java

Erlang

C, C++

Server operating systems

All OS with a Java VM

hosted

Linux

included in appliance

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

SQL

Support of SQL

yes

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC

RESTful HTTP/JSON API

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC
OLE DB

CLI Client
JDBC
ODBC

Supported programming languages

Java

C#
Java
JavaScript
Objective-C
PHP
Ruby

C++
Java
JavaScript (Node.js)
Python

C
C++
Fortran
Java
Lua
Perl
Python
R

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Java Stored Procedures

View functions (Map-Reduce) in JavaScript

user defined functions

yes

user defined functions

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

Source-replica replication

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 or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

atomic operations within a document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

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

GPU vRAM or System RAM

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users can be defined per database

Access rights for users and roles on table level

Users with fine-grained authorization concept

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

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