DBMS > DataFS vs. Infobright vs. Netezza
System Properties Comparison DataFS vs. Infobright vs. Netezza
Please select another system to include it in the comparison.
|Editorial information provided by DB-Engines
|DataFS Xexclude from comparison
|Infobright Xexclude from comparison
|Netezza Also called PureData System for Analytics by IBM Xexclude from comparison
|All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.
|High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend
|Data warehouse and analytics appliance part of IBM PureSystems
|Primary database model
|Object oriented DBMS
|Secondary database models
|Ignite Technologies Inc.; formerly InfoBright Inc.
|1.1.263, October 2022
|License Commercial or Open Source
|commercial The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016
|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.
|Server operating systems
|Linux included in appliance
|Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)
|Typing predefined data types such as float or date
|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.
|no Knowledge Grid Technology used instead
|SQL Support of SQL
|APIs and other access methods
|.NET Client API
Proprietary client DLL
|Supported programming languages
|Server-side scripts Stored procedures
|no, except callback-events from server when changes happened
|Partitioning methods Methods for storing different data on different nodes
|Proprietary Sharding system
|Replication methods Methods for redundantly storing data on multiple nodes
|MapReduce Offers an API for user-defined Map/Reduce methods
|Consistency concepts Methods to ensure consistency in a distributed system
|Foreign keys Referential integrity
|Transaction concepts Support to ensure data integrity after non-atomic manipulations of data
|Concurrency Support for concurrent manipulation of data
|Durability Support for making data persistent
|In-memory capabilities Is there an option to define some or all structures to be held in-memory only.
|User concepts Access control
|fine grained access rights according to SQL-standard exploiting MySQL or PostgreSQL frontend capabilities
|Users with fine-grained authorization concept
More information provided by the system vendor
We invite representatives of system vendors to contact us for updating and extending the system information,
Related products and services
We invite representatives of vendors of related products to contact us for presenting information about their offerings here.
|Netezza Also called PureData System for Analytics by IBM
|Recent citations in the news
AWS and IBM Netezza come out in support of Iceberg in table format face-off
U.S. Navy Chooses Yellowbrick, Sunsets IBM Netezza
Migrating your Netezza data warehouse to Amazon Redshift | Amazon Web Services
IBM Brings Back a Netezza, Attacks Yellowbrick
provided by Google News
Share this page