Vivaldi Web Browser

Startup Vivaldi Technologies debuted a new browser,This is company is founded by  ‘Jon Stephenson von Tetzchner’ former co-founder & CEO of Opera.



 A freeware web browser that not only fast but rich in features & functionality. In this browser Opera’s Presto engine is switched to Blink.  This browser is available for Linux, Windows and OS X. Within 10 days of release, more than 5,00,000 download is noted.

Features of Vivaldi

1. Minimalistic interface with basic icons and fonts.
2. Browser color is based on background and elements of web page visited.
3. It is a freeware but not Opensource. To understand it you may assume free as in beer and not in speech.
4. Quick Commands : For those who prefer keyboard as input over other input devices, this feature lets user to search through various settings, tabs, bookmarks and history with a keyboard shortcut. This feature aims at allowing users to create their custom commands and run them as and when required.
5. Notes : This feature allows user to take notes while browsing and add screenshots. The notes will keep track of the website you were browsing while taking notes. Moreover you can add tags to the notes and organize so that it can be find later.
6. Speed Dials : A graphical blocks of favorite sites grouped together so that you can access them from a single window. The most powerful fact of this feature is you can add a folder to speed dial as well.
7. Tab Stacks : Group multiple tabs together using tab stack so that when an end user is working with too many unorganized tabs, things are not messy. This feature makes it possible to group multiple tabs into single thus organizing your work.
8. Built on Web Technologies : The building blocks of Vivaldi is unique in the sense that it is developed using web for web. The building blocks viz., Node.js – to browse, HTML5, JavaScript and ReactJS for user interface is enough to tell that the website is promising.
9. Higher level of customization : User can disable tab stacking, place tab bar at top/bottom left/right and change tab cycling order.
10. Site info : This feature provides you with the details of cookies and site data as well as let you view connection information, a security measure implementation.

OLTP Vs. OLAP

Online Transaction Processing

OLTP System deals with operational data. Operational data are those data  involved in the operation of a particular system.

Example: In a banking System, you withdraw amount from your account. Then Account Number, Withdrawal amount, Available Amount, Balance Amount, Transaction Number etc are operational data elementions.

    Operational Data
    Operational data are usually of local relevance
    Frequent Updates
    Normalized Tables
    Point Query

In an OLTP system data are frequently updated  and queried. So quick response to a request is highly expected. Since the OLTP systems invlove large number of update quiries, the database tables are optimized for write operations.

To prevent data redundancy and to prevent update anomalies the database tables are normalized.Set of tables that are normalized are fragmented.Normalization makes the write operation in the database tables more efficient.

Operational data are usually of local relevance.It involves Queries accessing individual tuple(individual record).These type of queries are termed as point queries.

Example :Bank account transaction

Online Analytical Processing (OLAP)

OLAP deals with Historical Data or Archival Data. Historical data are those data that are archived over a long period of time. Data from  OLTP are collected over a period of time and store it in a very large database called Data warehouse. The Data warehouses are highly optimized for read (SELECT) operation.

Example: If we collect last 10 years data about flight reservation, The data can give us many meaningful information such as the trends in reservation. This may give useful information like peak time of travel, what kinds of people are traveling in various classes (Economy/Business)etc.

Analytical Query: Online Analytical Processing (OLAP) quries are of  analytical form. Query need to access large amount of data and require huge number of aggregations. It access large number of records from database tables and perform the required operation based on this.

    Historical Data or Archival Data
    Infrequent updates
    Analytical queries require huge number of aggregations
    Integrated data set with a global relevance

Updates are very rare in a Data warehouse.OLAP quiries will give aggregated information about the things happend in the past over a period of time and this will help the management in strategic decision making. Hence OLAP Queries are of  having  significant importance in strategic decision making.

Example: profit changing over the years across different regions