DBMS > Infobright vs. Netezza vs. ReductStore vs. SAP HANA

System Properties Comparison Infobright vs. Netezza vs. ReductStore vs. SAP HANA

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Editorial information provided by DB-Engines

Name

Description

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Data warehouse and analytics appliance part of IBM PureSystems

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	1.02
Rank	#192	Overall
	#90	Relational DBMS

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Score	0.05
Rank	#384	Overall
	#44	Time Series DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

ignitetech.com/softwarelibrary/infobrightdb

www.ibm.com/products/netezza

github.com/reductstore
www.reduct.store

www.sap.com/products/hana.html

Technical documentation

www.reduct.store/docs

help.sap.com/hana

Developer

Ignite Technologies Inc.; formerly InfoBright Inc.

IBM

ReductStore LLC

SAP

Initial release

2005

2000

2023

2010

Current release

1.9, March 2024

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

commercial

Open Source

Business Source License 1.1

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++, Rust

Server operating systems

Linux
Windows

Linux

included in appliance

Docker
Linux
macOS
Windows

Appliance or cloud-service

Data scheme

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.

Secondary indexes

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

JDBC
ODBC
OLE DB

HTTP API

JDBC
ODBC

Supported programming languages

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
C++
Fortran
Java
Lua
Perl
Python
R

C++
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

yes

SQLScript, R

Triggers

yes

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

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

Users with fine-grained authorization concept

yes

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