Monday, 19 December 2016

How and Why To Bridge between SQL and NoSQL

SQL have for long now been the synonym of "database" for us. For any sort of data management, SQL had been our instinctive choice. However, the past decade saw the emergence of NoSQL which gave rise to a fierce competition of preferences.
What haunts the mind of every aspiring database developer today is the question of choice: To SQL or NoSQL. We want to keep in touch with the latest trends in the technology, but don't want the established technologies to slip away either. However, the most basic point that most people seem to miss is this: SQL and NoSQL are not competitors, and most certainly not antonyms of each other.

SQL or Structured Query Language is the most standard concept of database management systems today. SQL considers data to be stored in the form of tables called Relations, that consist of tuples and attributes. While this concept had been a hugely successful improvement over the data-storage systems present at that time, like flat files, things have changed today.

NoSQL came as a breath of fresh air in an industry that was rapidly changing. The world is going digital, and the digital world is messy. We can never predict the volume, variety or velocity of incoming data. The data, apart from being unpredictable, is also unstructured. Since relational databases are not inherently adept to handle them, something else was required. At the same time, distributed computing is all the rage today, because most businesses are moving towards the cloud. The expansion of relational databases cannot keep up with the pace; thus, NoSQL entered into the scene.

Why to migrate from SQL to NoSQL

Strictly speaking, NoSQL aims to do what SQL cannot. It is not based on relations and it may sometimes even fail to follow the ACID properties! But unlike what you have been taught, ACID properties, though really useful, are not the ultimate necessity. The ultimate necessity is fault tolerance, and NoSQL manages to achieve that anyway.

NoSQL cannot be defined in a single line, as there is no single definition. While all SQL-based databases follow strict guidelines that adhere to SQL-standards, NoSQL gives the databases a free rein. With so many lacks of standards, one might wonder: Are the reasons enough to migrate to NoSQL?

Yes, because we have only touched the crux of the importance of NoSQL in modern world. The two biggest reasons why NoSQL trumps over SQL are agility and scalability.

With the rapid changes that occur daily in the industry, being agile is the only way to survive. However, Relational databases couldn't ever hope to achieve that, with their rigid schemas and complex development. The aforementioned rapid changes are also met by growing size, which require rapid scalability. However, scalability was one aspect that was blatantly ignored in SQL (as it was made in a time when web and internet were non-existent). To cope up with these issues, NoSQL seems like our best bet.

Why to Bridge SQL and NoSQL

"Now that we know how NoSQL differs from SQL, the question arises: Why to bridge them? Why not adopt NoSQL altogether?   "

Simply, because NoSQL doesn't have the same penetration as SQL. A huge number of companies have their entire existing architecture based on relational databases, which would be quite a headache to change. But that doesn't mean that one has to remain stuck with SQL forever. The best option in such scenarios is to bridge the existing SQL framework with a NoSQL database. The benefit? To put it simple, it will bring out "the best of both worlds".

As far the "bridging" goes, there is no one, simple way to do that. The easiest way would be to use third-party drivers like easysoft, which provides ODBC-like bridging capabilities. However, as it comes from a third-party vendor, it might have its own security and licensing issues.

An alternative approach would be to develop languages that could extend SQL functionality to NoSQL databases. One example would be the N1QL, introduced by Couchbase Server, which extends SQL to JSON.

The ways to bridge the gap between these two technologies may differ and evolve; but we can all agree that co-existence of the two is best for the progress of industry.

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Read more on NO SQL- NOT ONLY SQL here - WhatisNoSQL

Wednesday, 14 December 2016

Unix vs Linux: What Is The Difference?

The two terms look similar but there are significant differences between both.

Unix is a proprietary operating system created in 1970, although there are now free derivative versions. UNIX is usually favored for largescale environments like universities, big enterprises or companies. The proprietary version today has a number of variants that developed over time but are mostly based on one of original editions. A few of the top ones are - Sun's Solaris, Hewlett-Packard's HP-UX, Mac OS X and IBM's AIX®

“Linux is a free source version of the same idea of UNIX, behaving similarly but not a clone per se“

The development of Linux started off with a desire to have a free alternative to Unix. In early 1980s the GNU project developed a free version of Unix, and decided to adopt the kernel which was being written by Linus Torvalds. Linux in itself is only a kernel while Unix is a complete operating system with all components coming from a single source. Linux in conjunction with GNU Project is a complete system, and the code is freely available.

A few popular names in Linux Distribution (Operating System) are Redhat Enterprise Linux, Debian Linux, Fedora Linux, Suse Enterprise Linux, Ubuntu Linux

Understanding the Differences

Although they share the same foundations, Linux & Unix have a number of technical differences.Primarily commercial Unix versions remain largely consistent as they follow published standards, retaining established norms. Linux on the other hand is more diverse. Different developers have developed different versions modifying elements as required. This often makes it difficult for developers to switch between versions or keep track of changes.

Both software packages come with their own set of tools, firewall systems, backup software, and other applications.

A major difference is in the filesystems support. Linux was created for personal computer but it’s more flexible than UNIX as it supports far many more file-system types than UNIX. This flexibility has made Linux an extremely popular and powerful tool. Commercial Unix versions usually supports two or three filesystem types but Linux supports almost all the different filesystem types that are available under any form of operating system. Not surprisingly, Linux is today used on a wide variety of hardware ranging from mobile phones, or video game systems to supercomputers.

Linux has numerous forms of operating systems available– both free and paid. Cheaper than the commercial versions, the paid versions offer support, training and consultancy services.  For Unix, a commercial license would need to be procured for deploying the software.

Read more about UNIX - Unix inDetail

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Friday, 9 December 2016

7 Top Big Data Tools for Enterprise Developers

Big Data is now a critical technology utilized for leveraging data to enable better decision-making. Developers today have a wide variety of choice in picking a tool for their needs – open source or proprietary.

A through assessment of the existing data structure and the business requirements is essential for developers to identify the right tool. Predominant data formats, existing database types, available budget and the desired output analytics are some important factors. A few of the top tools that can be considered by developers are given below:

1.   MongoDB
This is an open source platform that that is heavily document oriented allowing for full-fledged indexing. Users can index any attribute and can also scale the data horizontally. Its a cross-platform tool that allows developers great control over final results

Read more about this at Mongo DB-Features         

A proprietary platform from tech giant SAP, HANA offers in-memory data storage that speeds up data processing and delivers more insightful data. It is flexible in handling all forms of data including spatial data, graph data and text data, at real time, making it a powerful though an expensive tool for holistic data analytics.

3.   Google Charts
A free open source platform from Google, this has a wide range of capabilities to handle data off a website. Primarily used for visualization, it can be plugged into a website with a simple JavaScript code. Developers can use it to create dashboards, carry out data management tasks, pull data from an external database, among other tasks

4.   Hadoop
Hadoop is the Big Data tool that everyone has been talking about. An open-source framework, it can handle, store and process massive amounts of data. Due to a distributed computing model, the data processing is fast and powerful. The tool is highly flexible and scalable, making it an ideal choice to leverage Big Data analytics for enormous data sets

Read more about this at Hadoop-Features

5.   Spark
Spark is an highly popular open-source data processing platform and is said to be the most active Apache open source project under Big Data. It is an extremely fast – 100x faster than Hadoop- and flexible platform, enabling analyses all forms of structured and unstructured data. Its advantages include use of multiple languages and accessibility to other databases. 

6.   Splice Machine
Splice Machine is a SQL-on-Hadoop database that analyses data in real time. The tool allows developers to utilize standard SQL on it, giving it flexibility and making it easier to use.
Splice Machine which is also ACID-compliant product is available on a freemium basis and has a list price annual license fee of $5,000 per node.

7.   Splunk
It’s a popular Advanced IT Search Tool used by many companies which derives information from machine data. To make it more lucid, Splunk has the ability to search, monitor and analyze through all machine generated data such as log data generated by applications, servers, and network devices across an organization.

This product further indexes structured as well as unstructured data and helps in diagnosing the problems, making it easy for administrators, business analysts and managers to detect requisite information.

Read more at Splunk-Features

Thursday, 1 December 2016

Oracle’s DYN Acquisition Fits Into Its Goal To Become A Cloud Leader

Last week tech giant Oracle announced that it was acquiring DYN, the popular cDNS provider, for an unspecified amount. Some reports have said that it could be in the region of $600-700 million.

DYN’s cloud-based platform manages and optimises the performance of internet applications and infrastructure by using analytics and intelligent routing. Its Internet performance and Domain Name System (DNS) solution is being used by over 3,500 companies that include top digital brands like Netflix, Twitter and Reddit.  On a daily basis, it handles over 40 billion traffic optimization decisions, making it one of the leading DNS service providers

For Oracle, buying DYN offers an opportunity to challenge the current leaders of cloud computing, Google Cloud.  Oracle currently lags significantly behind these companies in terms of the cloud computing market share, having primarily a portfolio that’s limited to datacentres systems. 

The Enterprises services leader does has a variety of Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS) products but adding DYN’s range of scalable services would help Oracle’s customers to get access to cutting edge traffic optimization technologies, filling a gap that might have taken far more time to plug with organic product development.

Oracle has pegged it as a natural extension to its cloud solutions – a service that is the link between hosting data and incoming traffic, resulting in improved metrics for access and user satisfaction for its clients.

This latest acquisition is in keeping with Oracles strategy of buying companies that have noteworthy products in cloud computing – it has in recent times acquired cloud-based applications firm LogFire, cloud access security broker Palerra as well as NetSuite the integrated cloud business software suite.  

If looked at the pattern of these acquisitions, it clearly show the intent of Oracle to move away from its legacy software-led business towards the cloud which in recent times has significantly reshaped how businesses and IT infrastructure are built and run.

It in fact has a stated goal to become the first tech company to reach $10 billion in revenue from cloud business. The NetSuite deal alone is expected to add close to $1 billion in revenue giving a boost to its cloud business.

"With the DYN acquisition, Oracle will be able surely to leapfrog into direct competition with leaders of cloud computing, and make an attempt at taking the leadership position in the market " . 

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