DBMS > FatDB vs. Netezza vs. Oracle NoSQL vs. Splice Machine

System Properties Comparison FatDB vs. Netezza vs. Oracle NoSQL vs. Splice Machine

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Data warehouse and analytics appliance part of IBM PureSystems

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Document store
Key-value store

Relational DBMS

Document store
Key-value store
Relational DBMS

Relational DBMS

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

Score	7.56
Rank	#48	Overall
	#31	Relational DBMS

Score	3.07
Rank	#86	Overall
	#15	Document stores
	#11	Key-value stores
	#47	Relational DBMS

Score	0.54
Rank	#244	Overall
	#114	Relational DBMS

Website

www.ibm.com/products/netezza

www.oracle.com/database/nosql/technologies/nosql

splicemachine.com

Technical documentation

docs.oracle.com/en/database/other-databases/nosql-database/index.html

splicemachine.com/how-it-works

Developer

FatCloud

IBM

Oracle

Splice Machine

Initial release

2012

2000

2011

2014

Current release

24.1, May 2024

3.1, March 2021

License

Commercial or Open Source

commercial

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

AGPL 3.0, 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

Java

Server operating systems

Windows

Linux

included in appliance

Linux
Solaris SPARC/x86

Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

Typing

predefined data types such as float or date

yes

optional

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.

Secondary indexes

yes

SQL

Support of SQL

Via inetgration in SQL Server

yes

SQL-like DML and DDL statements

yes

APIs and other access methods

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

JDBC
ODBC
OLE DB

RESTful HTTP API

JDBC
Native Spark Datasource
ODBC

Supported programming languages

C
C++
Fortran
Java
Lua
Perl
Python
R

C
C#
Go
Java
JavaScript (Node.js)
Python

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

yes

via applications

yes

Java

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate 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

configurable

ACID within a storage node (=shard)

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

off heap cache

yes

User concepts

Access control

Can implement custom security layer via applications

Users with fine-grained authorization concept

Access rights for users and roles

Access rights for users, groups and roles according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Unify and share data across Netezza and watsonx.data for new generative AI applications
21 June 2024, IBM

How to migrate a large data warehouse from IBM Netezza to Amazon Redshift with no downtime
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

provided by Google News

OpenWorld 2013: Oracle NoSQL Database On the Rise?
13 December 2023, Channel Futures

Cloud database comparison: AWS, Microsoft, Google and Oracle
24 July 2024, TechTarget

Top 8 Best NoSQL Databases in 2024
9 September 2024, AIM

Explore Oracle Database Solutions for Maximum Efficiency
4 September 2018, Oracle

NoSQL Rebels Aim Missile at Larry Ellison's Yacht
20 July 2012, WIRED

provided by Google News

Machine learning data pipeline outfit Splice Machine files for insolvency
26 August 2021, The Register

Splice Machine Launches the Splice Machine Feature Store to Simplify Feature Engineering and Democratize Machine Learning
19 January 2021, PR Newswire

2021: The Year of the Feature Store
19 January 2021, Datanami

Monte Zweben's Splice Machine Introduces New Hadoop RDBMS
24 June 2014, Forbes

Splice Machine Launches ML Manager Beta Program to Meet the Growing Demand for Operational AI
7 April 2019, insideBIGDATA

provided by Google News

Share this page