Magic
Quadrant's definition: a data management solution for analytics is a complete
software system that supports and manages data in one or many disparate file
management systems (most commonly a database or multiple databases) that can
perform relational processing (even if the data is not stored in a relational
structure) and support access and data availability from independent analytic
tools and interfaces.
Teradata
(TD, AsterData, UDA suite), IBM (PureData.. Netezza), Oracle (Exadata ..Oracle
Big Data Appliance), SAP (IQ & Hana), Microsoft (SQL Server Parallel Data
Warehouse and HDInsight) & HP (Vertica, Autonomy) are in the leader's
quadrant of "Magic Quadrant for Data Warehouse and Data Management Solutions
for Analytics 2015" considering following criteria by Gartner:
- Relational data management.
- Non-relational data management.
- No specific rating advantage is
given regarding the type of data store used (for example, RDBMS, HDFS,
key-value, document; row, column and so on).
- Multiple solutions in combination
to form a DMSA are considered valid (although one approach is adequate for
inclusion), but each solution must demonstrate maturity and customer
adoption.
- Cloud solutions (such as PaaS) are
considered viable alternatives to on-premises warehouses; and ability to
manage hybrids between premises and the cloud are considered advantageous.
- DMSAs are expected to coordinate
data virtualization strategies for accessing data outside of the DBMS, as
well as distributed file and/or processing approaches.
Many solutions for management of enterprise data promise the moon and show all kinds of direct and indirect solutions to lure the client. The problem is that most organizations do not know how to make the best use of expensive technologies available for managing data.
ReplyDeleteTIMG Australia provide best data management solutions
This comment has been removed by the author.
ReplyDelete