HTML5 is a markup language for structuring and presenting content
for the World Wide Web, and is a core technology of the Internet originally
proposed by Opera Software. It is the fifth revision of the HTML standard
(created in 1990 and standardized as HTML4 as of 1997) and, as of June 2012,
is still under development. Its core aims have been to improve the language with
support for the latest multimedia while keeping it easily readable by humans and
consistently understood by computers and devices (web browsers, parsers, etc.).
HTML5 is intended to subsume not only HTML 4, but XHTML 1 and DOM Level 2 HTML
HTML or Hypertext Markup Language is a formatting language that
programmers and developers use to create documents on the Web. The latest
edition HTML5 has enhanced features for programmers such as <video>,
<audio> and <canvas> elements. You view a Web page written in HTML
in a Web browser such as Internet Explorer, Mozilla Firefox or Google Chrome.
The HTML5 language has specific rules that allow placement and format of text,
graphics, video and audio on a Web page. Programmers use these programming tags
or elements to produce web pages in unique and creative ways. Tags such as
<section>, <article>, <header> enable the creator to make a
more efficient and intelligent web page. Users will not have to use a Flash
plug-in for video and audio content. Visual Studio users typically write code in
HTML5 when creating web site content.
In computing, NoSQL
(sometimes expanded to "not only SQL") is a broad class of database management
systems that differ from the classic model of the relational database management
system (RDBMS) in some significant ways, most important being they do not use
SQL as their query language. These data stores may not require fixed table
schemas, usually avoid join operations, and typically scale horizontally.
Academic researchers typically refer to these databases as structured storage, a
term that includes classic relational databases as a subset.
NoSQL databases are
categorized according to the way they store the data and it falls under
categories such as Key-Value stores, BigTable Implementations, Document-Store
databases and Graph Database. NoSQL database systems rose alongside major
internet companies, such as Google, Amazon, Twitter and Facebook which had
significantly different challenges in dealing with data that the traditional
RDBMS solutions could not cope with. With the rise of real-time
web there was a need to provide curated information out of large volumes of data
which more or less followed similar horizontal structures. These companies
realized that performance and real time nature was more important than
consistency, which traditional relational databases were spending a high amount
of processing time to achieve.
It has been
predicted that in memory computing will be one of the Top 10 technologies of
database (IMDB; also main memory database system or MMDB) is a database
management system that primarily relies on main memory for computer data
storage. It is contrasted with database management systems which employ a disk
storage mechanism. Main memory databases are faster than disk-optimized
databases since the internal optimization algorithms are simpler and execute
fewer CPU instructions. Accessing data in memory reduces the I/O reading
activity when querying the data which provides faster and more predictable
performance than disk. In applications where response time is critical, such as
telecommunications network equipment and mobile ads networks, main memory
databases are often used.
Data Partitioning is
the formal process of determining which data subjects, data occurrence groups,
and data characteristics are needed at each data site. It is an orderly process
for allocating data to data sites that is done within the same common data
Data Partitioning is also the process of logically and/or physically
partitioning data into segments that are more easily maintained or accessed.
Current RDBMS systems provide this kind of distribution functionality.
Partitioning of data helps in performance and utility processing.
Data Partitioning can be of great help in facilitating the efficient and
effective management of highly available relational data warehouse. But data
partitioning could be a complex process which has several factors that can
affect partitioning strategies and design, implementation, and management
considerations in a data warehousing environment.
A data warehouse which is powered by a relational database management system can
provide for a comprehensive source of data and an infrastructure for building
Business Intelligence (BI) solutions. Typically, an implementation of a
relational data warehouse can involve creation and management of dimension
tables and fact tables. A dimension table is usually smaller in size compared to
a fact table but they both provide details about the attributes used to describe
or explain business facts. Some examples of a dimension include item, store, and
time. On the other hand, a fact table represents a business recording like item
sales information for all the stores. All fact table need to be periodically
updated using data which are the most recently collected from the various data
Since data warehouses need to manage and handle high volumes of data updated
regularly, careful long term planning is beneficial. Some of the factors to be
considered for long term planning of a data warehouse include data volume, data
Index maintenance window, workload characteristics, data aging strategy, archive
and backup strategy and hardware characteristics
There are two approaches to implementing a relational data warehouse: monolithic
approach and partitioned approach. The monolithic approach may contain huge fact
tables which can be difficult to manage.
There are many benefits to implementing a relational data warehouse using the
data partitioning approach. The single biggest benefit to a data partitioning
approach is easy yet efficient maintenance. As an organization grows, so will
the data in the database. The need for high availability of critical data while
accommodating the need for a small database maintenance window becomes
indispensable. Data partitioning can answer the need to small database
maintenance window in a very large business organization. With data
partitioning, big issues pertaining to supporting large tables can be answered
by having the database decompose large chunks of data into smaller partitions
thereby resulting in better management. Data partitioning also results in faster
data loading, easy monitoring of aging data and efficient data retrieval system.
Data partitioning in relational data warehouse can implemented by objects
partitioning of base tables, clustered and non-clustered indexes, and index
views. Range partitions refer to table partitions which are defined by a
customizable range of data. The end user or database administrator can define
the partition function with boundary values, partition scheme having file group
mappings and table which are mapped to the partition scheme.
(database) - Wikipedia, the free encyclopedia
Partitioning in Postgresql
SQL Server Database Table
On the Internet,
pagination is used for such things as displaying a limited number of results on
search engine results pages, or showing a limited number of posts when viewing a
forum thread. Pagination is used in some form in almost every web application to
divide returned data and display it on multiple pages. Pagination also includes
the logic of preparing and displaying the links to the various pages.
Pagination can be handled client-side or server-side. Server-side pagination is
more common. Client-side pagination can be used when there are very few records
to be accessed, in which case all records can be returned, and the client can
request the subsequent page which is loaded and inserted into the Document
Object Model via AJAX.
Server-side pagination is appropriate for large data sets providing faster
view business logic
Correctly implementing pagination can be difficult. There are many different
usability questions such as should "previous" and "next" links be included, how
many links to pages should be displayed, and should there be a link to the first
and last pages. Also ability to define the number of records displayed in a
single page is useful.
A content management system (CMS) is a system providing a
collection of procedures used to manage work flow in a collaborative
environment. These procedures can be manual or computer-based. The procedures
are designed to do the following:
- Allow for a large number of people to contribute to and share stored
- Control access to data, based on user roles (defining which information
users or user groups can view, edit, publish, etc.)
- Aid in easy storage and retrieval of data
- Control of data validity and compliance
- Reduce repetitive duplicate input
- Improve the ease of report writing
- Improve communication between users
WebDNA: an incredibly flexible scripting
language and database system..
WebDNA is a FREEWARE; it is an easy to learn server-side
scripting language specifically designed for the World Wide Web, with an
embedded hybrid in-memory database system. It allows to easily build
WebDNA is a general-purpose server-side scripting language and
database system designed for web development to produce dynamic database-based
web pages. For this purpose, WebDNA code is embedded into the HTML source
document and interpreted by a web server with a WebDNA FastCGI processor, which
generates the web page document. WebDNA allows the developer to build a wide
range of applications, from very basic form-to-email to highly sophisticated
database-driven intranet sites. Very easy to learn, a single easy to understand
WebDNA instruction would replace complex php or asp code. A developer can
typically complete 3 WebDNA sites in the time it takes to achieve one with php
WebSphere Application Server ..
WebSphere Application Server delivers a faster, more flexible
development environment along with intelligent management capabilities for
WebSphere Application Server provides a fast, flexible and
simplified environment for application development and administration along with
new intelligent management capabilities for enhanced resiliency. From business
critical and key enterprise-wide applications to the smallest departmental level
applications, WebSphere Application Server offers the highest levels of
reliability, availability, security and scalability.
A scalable application foundation that can go from single server to moderately
sized departmental configurations to large-scale, dynamic web applications
requiring web tier clustering and fail over across multiple application server
Optimize developer productivity and web application deployment with the new
Liberty Profile option, an ultra lightweight, fast starting, highly composable
application server profile.
Improve productivity and resiliency while gaining interruption free rollout
without incurring outages to your end users with Application Edition Management
Realize higher application availability to end users with new Application
Health Management that monitors the status of your application servers and
senses and responds to problem areas before end users suffer and outage.
Improve business results by ensuring priority is given to business critical
applications with new Intelligent Routing features that prioritizes and routes
requests based upon administrator defined rules.
Handle spikes in demand and dynamically provision and start and stop new
instance of application server Java Virtual Machines (JVMs) based on workload
Gain higher quality of service by leveraging a common Java infrastructure
for OLTP and batch applications with new Enterprise Batch Workload support that
can be executed across multiple Java EE environments.
Developer tool options to match project development needs, support for Java
7,and OSGi, enhanced Migration Toolkit support, Support for the Web 2.0 and
A variety of pricing alternatives, including socket-based pricing