DBMS > EXASOL vs. Hive vs. Netezza vs. Snowflake vs. Sphinx

System Properties Comparison EXASOL vs. Hive vs. Netezza vs. Snowflake vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

data warehouse software for querying and managing large distributed datasets, built on Hadoop

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

Primary database model

Relational DBMS

Search engine

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

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

www.exasol.com

hive.apache.org

www.ibm.com/products/netezza

www.snowflake.com

sphinxsearch.com

Technical documentation

www.exasol.com/resources

cwiki.apache.org/confluence/display/Hive/Home

docs.snowflake.net/manuals/index.html

sphinxsearch.com/docs

Developer

Exasol

Apache Software Foundation

initially developed by Facebook

IBM

Snowflake Computing Inc.

Sphinx Technologies Inc.

Initial release

2000

2012

2000

2014

2001

Current release

3.1.3, April 2022

3.5.1, February 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

commercial

Open Source

GPL version 2, commercial licence available

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++

Server operating systems

All OS with a Java VM

Linux

included in appliance

hosted

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

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.

yes

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

yes

SQL-like DML and DDL statements

yes

SQL-like query language (SphinxQL)

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

JDBC
ODBC
Thrift

JDBC
ODBC
OLE DB

CLI Client
JDBC
ODBC

Proprietary protocol

Supported programming languages

Java
Lua
Python
R

C++
Java
PHP
Python

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

Server-side scripts

Stored procedures

user defined functions

yes

user defined functions and integration of map-reduce

yes

user defined functions

Triggers

yes

similar concept for controling cloud resources

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

selectable replication factor

Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

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.

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

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

Access rights for users, groups and roles

Users with fine-grained authorization concept

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

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