DBMS > GigaSpaces vs. Netezza vs. Snowflake vs. Sphinx vs. Valentina Server

System Properties Comparison GigaSpaces vs. Netezza vs. Snowflake vs. Sphinx vs. Valentina Server

Editorial information provided by DB-Engines

Name

Description

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

Data warehouse and analytics appliance part of IBM PureSystems

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

Open source search engine for searching in data from different sources, e.g. relational databases

Object-relational database and reports server

Primary database model

Document store
Object oriented DBMS

Values are user defined objects

Relational DBMS

Search engine

Relational DBMS

Secondary database models

Graph DBMS
Search engine

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

Score	1.03
Rank	#188	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Website

www.gigaspaces.com

www.ibm.com/products/netezza

www.snowflake.com

sphinxsearch.com

www.valentina-db.net

Technical documentation

docs.gigaspaces.com/latest/landing.html

docs.snowflake.net/manuals/index.html

sphinxsearch.com/docs

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Gigaspaces Technologies

IBM

Snowflake Computing Inc.

Sphinx Technologies Inc.

Paradigma Software

Initial release

2000

2014

2001

1999

Current release

15.5, September 2020

3.5.1, February 2023

5.7.5

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial licenses available

commercial

Open Source

GPL version 2, commercial licence available

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, C++, .Net

C++

Server operating systems

Linux
macOS
Solaris
Windows

Linux

included in appliance

hosted

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

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

yes

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.

XML can be used for describing objects metadata

yes

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

SQL-99 for query and DML statements

yes

SQL-like query language (SphinxQL)

yes

APIs and other access methods

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

JDBC
ODBC
OLE DB

CLI Client
JDBC
ODBC

Proprietary protocol

ODBC

Supported programming languages

.Net
C++
Java
Python
Scala

C
C++
Fortran
Java
Lua
Perl
Python
R

JavaScript (Node.js)
Python

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

yes

user defined functions

yes

Triggers

yes, event driven architecture

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

Foreign keys

Referential integrity

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

The original contents of fields are not stored in the Sphinx index.

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

Role-based access control

Users with fine-grained authorization concept

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

fine grained access rights according to SQL-standard

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