Oracle Exdata

Exdata is a hardware machine which runs oracle database; supports OLTP, Database

Exologic is a hardware machine for application and primarily for cloud computing

Exadata X2-2 Hardware Architecture (FULL Rack)

DBA's has to think about storage server, DB server, storage connecting devices, fiber channel connectivity, Network components, OS, storage drives this all includes in Exdata

In Storage Grid of Exdata it contains 2 Xenon CPU with computing power which take care of processing inside the storages 

Flash is the key performance of Exdata machine. Its a kind of h/w in a pci slot where all your data is stored intermediately between db server and storage server. 

InfiniBand Networks (fiber channel has only 10gb/s) which is also a key performance of Exdata ;which used to transfer data between db server to storage which has high bandwidth

In Exdata is a preconfigured plug and play software .

Key Performance of Exdata

1)      Intelligent Storage Grid

2)      Hybrid Columnar Compression will compress 10 times the data

3)      Smart Flash Cache (patented product of Oracle) different from SSD; it’s a second SGA at storage level which also contains algorithm which drives the flash cache.

In Traditional San if we increase the storage it will not increase the db performance because the spindles of hardware will perform as usual to read from storage

In Exdata there storage is intelligent.  (www.tpc.org to get which is the fastest machine)

ROW level locking

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it means any moment of time any person can do DML at a moment of time so entire table is locked ,so oracle introduced rowlevel locking mechanism which makes oracle faster

Rowlevel is managed at block level ultimate storage element of ur row.

RMAN is the backup in exdata

Database vs Data warehouse

Similarities in Database and Data warehouse:

* Both database and data warehouse are databases.
* Both database and data warehouse have some tables containing data.
* Both database and data warehouse have indexes, keys, views etc.

Differences

* The Application database is not your Data Warehouse for the simple reason that your application database is never designed to answer queries.

* The database is designed and optimized to record while the data warehouse is designed and optimized to respond to analysis questions that are critical for your business.

* Application databases are On-Line Transaction processing systems where every transition has to be recorded, and super-fast at that.

* A Data Warehouse on the other hand is a database that is designed for facilitating querying and analysis

* A data warehouse is designed as On-Line Analytical processing systems . A data warehouse contains read-only data that can be queried and analyzed far more efficiently as compared to regular OLTP application databases. In this sense an OLAP system is designed to be read-optimized.

* Separation from your application database also ensures that your business intelligence solution is scalable, better documented and managed and can answer questions far more efficiently and frequently.

Data warehouse is better than a database:

The Data Warehouse is the foundation of any analytics initiative. You take data from various data sources in the organization, clean and pre-process it to fit business needs, and then load it into the data warehouse for everyone to use. This process is called ETL which stands for ‘Extract, transform, and load'.

Suppose you are running your reports off the main application database. Now the question is would the solution still work next year with 20% more customers, 50% more business, 70% more users, and 300% more reports? What about the year after next? If you are sure that your solution will run without any changes, great!! However, if you have already budgeted to buy new state-of-the-art hardware and 25 new Oracle licenses with those partition-options and the 33 other cool-sounding features, you might consider calling up Oracle and letting them know. There's a good chance they'd make you their brand ambassador.

Creation of a data warehouse leads to a direct increase in quality of analyses as you can keep only the needed information in simpler tables, standardized, and denormalized to reduce the linkages between tables and the corresponding complexity of queries.

A data warehouse drastically reduces the cost-per-analysis and thus permits more analysis per FTE.


(Data Adopted)