DW Product | IBM - DB2 Data Warehouse | Oracle - Exadata | Teradata |
Company | IBM has four major businesses:
hardware, software, services, and financing. Data warehousing is part of the data management business, which is part of the software business. | Oracle has three businesses: database,
applications, and consulting. Its database business is the largest by far and currently represents 80 percent of Oracles new license revenues. | NCR has four businesses: data
warehousing, financial self-service, retail store automation, and customer services. The Teradata Division is responsible for the data warehousing business |
Product URL | www.ibm.com/DataWarehousing | https://www.oracle.com/database/data-warehouse/index.html | www.teradata.com/ |
STRENGTHS | - Rich and flexible data partitioning capabilities -strong analytic functionality in OLAP and data mining - Market presence - Data Models - Hardware bundle - Partner network - Strong services arm (IBM GSA) | - Intelligent
Storage Grid - Hybrid Columnar Compression - Smart Flash Cache | - Massively-parallel, partitioned, - Shared-nothing database server architecture - its simple and highlyautomated physical data warehouse implementation -set of indexing approaches that enable fast access to data - scalable hybrid-storage capabilities - Teradata has buddied up with all enterprise Hadoop distro providers, enabled new analytic workloads to be added to Teradata systems (JSON, geospatial, 3D geospatial and others) and more. |
WEAKNESSES | - complex physical implementation - lack of integration with multidimensional - High cost of ownership - DB2 on the open systems platforms continues to suffer from locking problems. • Closed systems; can’t easily ride cost curves associated with commodity hardware. • Expensive fault tolerant solution compared with Exadata | - its incomplete visual tools for build and manage functionality - Proprietary hardware - Costly to maintain and upgrade - Limited skilled implementation expertise | |
Deployment Platforms | IBM AIX Microsoft Windows Linux Sun Solaris | IBM AIX Hewlett-Packard HP-UX Linux Microsoft Windows Sun Solaris | NCR SVR4 UNIX MP-RAS Microsoft Windows |
Server Architecture | Server platform with a single processor
Single database partition on a server platform with a multiple processors Multiple partition configurations Shared-nothing Multiple server platforms Server interconnect Any number of readers and writers | Single server platform
Distributed database Real Application Cluster (RAC) Shared, partitioned data Multiple server platforms Server interconnect Any number of readers and writers | Single and multiple node organization where a node is a hardware and software platform specialized and dedicated to data warehousing Teradata Warehouse is a sharednothing architecture in both its single and multiple node configurations |
Data Type Support | SQL types:
Numeric Binary Character Date time DATALINK XML Large objects (max 2 gigabytes) User-defined types (distinct renamed SQL types, structured object oriented, reference hierarchies of built-in types) | Oracle built-in data types (SQL
types): Numeric Binary Character Date time Large objects (max 2 gigabytes) User-defined types (object-oriented types, object identifier types, arrays, nested tables) Oracle-supplied types Spatial Media Text XML | SQL types:
Numeric Binary Character Date time Large objects |
Physical Design
Recommendation | Neutral on the physical design
of data warehouses. | Neutral on the physical design
of data warehouses. | Teradata is neutral on the physical
design of data warehouses but recommends a physical design of third normal form for data warehouses to maximize flexibility. Teradata further recommends that denormalized structures be implemented as views or redundant structures (logical data marts or special purpose tables). |
Physical Implementation | Manual | Manual
Template-based via templates and Database Configuration Assistant (DBCA) tool Automated via Oracle managed files | Automated |
Custom Transformations | May be written in:
SQL Java C++ | May be written in:
SQL PL/SQL | May be written in:
SQL C++ |
Summary Table Support | Materialized query tables automate
the creation and management of summary tables. A materialized query table stores the results of a query in a table | Materialized views automate the
creation and management of summary tables. A materialized view stores the results of a query in a table | The OLAP transformations of
Teradata Warehouse Miner can create and manage summary tables. |
SQL Extensions | CUBE and ROLLUP in SELECT
Functions Aggregate Numeric Statistical Correlation Random number generation Regression Date time User-defined | CUBE and ROLLUP in SELECT
Functions Ranking Window aggregate Reporting aggregate Lag/lead Linear regression Inverse percentile Hypothetical rank and distribution First/last Numeric Date time User-defined | QUALIFY, SAMPLE, and WITH in
SELECT Functions and operators Aggregate Numeric Date time OLAP |
OLAP | DB2 provides OLAP build and
manage capabilities, relational OLAP on DB2 tables, and multidimensional and hybrid OLAP on a combination of DB2 tables and external multidimensional structures. DB2 OLAP Server is a separately- priced and -packaged product that is an external, but tightly integrated, multidimensional OLAP facility that IBM OEMs from Hyperion Solutions. | Oracle OLAP is a separatelypackaged
and -priced product that provides OLAP functionality | Provides relational OLAP on Teradata
Warehouse tables |
Data Mining | DB2 Intelligent Miner is bundled
with DB2 Data Warehouse Enterprise Edition. | Oracle Data Mining is a separately-
priced and -packaged product. | Teradata Warehouse Miner is a
separately-packaged and -priced product that is tightly integrated with Teradata Warehouse. |
This blog is useful for Database, Business Intelligence, Bigdata and Data Science professionals.
January 13, 2016
Data Warehouse - Copmarision Matrix
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