DBMS > Kinetica vs. Netezza vs. RavenDB vs. STSdb

System Properties Comparison Kinetica vs. Netezza vs. RavenDB vs. STSdb

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Editorial information provided by DB-Engines

Name

Description

Fully vectorized database across both GPUs and CPUs

Data warehouse and analytics appliance part of IBM PureSystems

Open Source Operational and Transactional Enterprise NoSQL Document Database

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Relational DBMS

Document store

Key-value store

Secondary database models

Spatial DBMS
Time Series DBMS

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Score	2.92
Rank	#101	Overall
	#18	Document stores

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

www.kinetica.com

www.ibm.com/products/netezza

ravendb.net

github.com/STSSoft/STSdb4

Technical documentation

docs.kinetica.com

ravendb.net/docs

Developer

Kinetica

IBM

Hibernating Rhinos

STS Soft SC

Initial release

2012

2000

2010

2011

Current release

7.1, August 2021

5.4, July 2022

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open Source

AGPL version 3, commercial license available

Open Source

GPLv2, commercial license available

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, C++

Server operating systems

Linux

included in appliance

Linux
macOS
Raspberry Pi
Windows

Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

SQL-like DML and DDL statements

yes

SQL-like query language (RQL)

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC
OLE DB

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

.NET Client API

Supported programming languages

C++
Java
JavaScript (Node.js)
Python

C
C++
Fortran
Java
Lua
Perl
Python
R

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

C#
Java

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

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

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID, Cluster-wide transaction available

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

GPU vRAM or System RAM

User concepts

Access control

Access rights for users and roles on table level

Users with fine-grained authorization concept

Authorization levels configured per client per database

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More resources

Recent citations in the news

Kinetica Elevates RAG with Fast Access to Real-Time Data
26 March 2024, Datanami

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21 March 2024, insideBIGDATA

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1 August 2023, The Register

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27 May 2020, AWS Blog

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