Python – The Coder’s Marathon Tool

Python is a general-purpose interpreted, interactive, object-oriented, and high-level programming language. It was created by Guido van Rossum during 1985- 1990. Like Perl, Python source code is also available under the GNU General Public License (GPL).

Today, we bring to you 10 advantages that you might have not known about Python.

1. Easy Syntax

Python’s syntax is easy to learn, so both non-programmers and programmers can start programming right away.

2. Readability

Python’s syntax is very clear, so it is easy to understand program code. (Python is often referred to as “executable pseudo-code” because its syntax mostly follows the conventions used by programmers to outline their ideas without the formal verbosity of code in most programming languages; in other words syntax of Python is almost identical to the simplified “pseudo-code” used by many programmers to prototype and describe their solution to other programmers. Thus Python can be used to prototype and test code which is later to be implemented in other programming languages).

3. High-Level Language

Python looks more like a readable, human language than like a low-level language. This gives you the ability to program at a faster rate than a low-level language will allow you.

4. Object oriented programming

Object-oriented programming allows you to create data structures that can be re-used, which reduces the amount of repetitive work that you’ll need to do. Programming languages usually define objects with namespaces, like class or def, and objects can edit themselves by using keyword, like this or self. Most modern programming languages are object-oriented (such as Java, C++, and C#) or have support for OOP features (such as Perl version 5 and later). Additionally object-oriented techniques can be used in the design of almost any non-trivial software and implemented in almost any programming or scripting language. (For example a number of Linux kernel features are “objects” which implement their own encapsulation of behavior and data structive via pointers, specifically pointers to functions, in the C programming language).

Python’s support for object-oriented programming is one of its greatest benefits to new programmers because they will be encountering the same concepts and terminology in their work environment. If you ever decide to switch languages, or use any other for that fact, you’ll have a significant chance that you’ll be working with object-oriented programming.

5. It’s Free

Python is both free and open-source. The Python Software Foundation distributes pre-made binaries that are freely available for use on all major operating systems called CPython. You can get CPython’s source-code, too. Plus, you can modify the source code and distribute as allowed by CPython’s license.

6. Cross-platform

Python runs on all major operating systems like Microsoft Windows, Linux, and Mac OS X.

7. Widely Supported

Python has an active support community with many web sites, mailing lists, and USENET “netnews” groups that attract a large number of knowledgeable and helpful contributes.

8. It’s Safe

Python doesn’t have pointers like other C-based languages, making it much more reliable. Along with that, errors never pass silently unless they’re explicitly silenced. This allows you to see and read why the program crashed and where to correct your error.

9. Batteries Included

Python is famous for being the “batteries are included” language.

There are over 300 standard library modules which contain modules and classes for a wide variety of programming tasks.

10. Extensible

In addition to the standard libraries there are extensive collections of freely available add-on modules, libraries, frameworks, and tool-kits. These generally conform to similar standards and conventions; for example almost all of the database adapters (to talk to almost any client-server RDBMS engine such as MySQL, Postgres, Oracle, etc) conform to the Python DBAPI and thus can mostly be accessed using the same code. So it’s usually easy to modify a Python program to support any database engine.

Apache Lucene – High Performance Guaranteed

Apache Lucene is a high performance search and information retrieval technology. The basic language behind this open source search technology is Java Script and it is all compatible with all the applications which require a full text search, especially, in cross-platform. Due to its high performance, scalability and relevancy, many bigshot organizations like IBM, AOL and Comcast Interactive Media bank upon it.

Currently, it is the powerful tool, running successfully all over the world. It also has great contributors, contributing from all around the world. Some of them are CNET, APPLE, Linkedin, IBM, Monster, MySpace, etc.

Why is Lucene the number one searched technology?

There are many specific features of Apache Lucene; let us discuss its 3 most powerful advantages:

1-Speed and high performance indexing

In terms of speed, there is none that can match Apache Lucene. This benefit is due to its Java framework. It only takes sub-seconds to result a query and this makes it very effective solution for any organization. It has great parameters to stand out from the crowd and efficiency is what, that makes it likable of all business players. As the speed increases, so does the overall performance. It also has a very small requirement of RAM, maximum 1MB. Also, its incremental indexing is faster than batch indexing.

2-Efficient and accurate search algorithms

In terms of Algorithm, it has ranked highest with best results returning first. In fact, to support the most accurate search, it features power queries including proximity queries, phrase queries, range queries and wild card queries. The option of field searching is available and you can start the search even by the name of author, title, and other search terms.

To elevate accuracy in the search function, it has multiple-index search features with merges results. It allows searching and updating simultaneously to provide the best results. Some of the pluggable ranking models used by Apache Lucene are OkapiBM25 and Vector Space Model. It also provides features like highlighting, flexible faceting, and result grouping.

3-Open source and cross Platform

Apache Lucene an open source program by Apache Software Foundation. It is currently free for all types of usage, including the open source programing and commercial purposes. There is no initial cost of the software and hence, it is quite benefiting for the businesses which are too new to input funds in software development, etc. Also, besides it has 100% javascript, it can still be implemented in other programming languages as well. However, the other implemented language should be index-compatible.

In fact, Apache Lucene provides complete source code so that the organization, using it at user end, does not need to re-write its own code. In fact, the most interesting fact is that, Lucene has forums for discussing the shortcomings while handling it. You can actively participate in discussions to help resolve other’s issues or get cleared off yours.

Apache Lucene has quickly emerged as a search technology of the latest generation packed with an array of powerful features. So, with the 3 above mentioned advantages, it certainly makes the best open source software to be used by any organization.

Amazon Is Really Prime

There is a myriad of reasons about why most businesses use Amazon Web Services. Amazon offers with top-notch cloud hosting services that are better than most of regular cloud hosting services. Let us look into top five reasons that make this incredible service so popular with businesses irrespective of scale or size.

1. Performance

There are certain factors, which a business requires while getting a web hosting service. The factors are significant performance, optimal security, quick disaster recovery, 24/7 management and flexibility. These factors save a lot of time and money being invested in a business and offer 99.99% reliability with seamlessly automated working. Well, AWS has all these factors and that is why, it is a class apart from other service providers.

2. Cost effective

When looking around for web services, every business needs something that is cost effective and affordable. The amount of money that a business saves with web services can be used in other areas like for gaining traffic and conversion rates.

Amazon Web Services offers convenience where a business has a complete control over its resources. When needed, they can switch on the auto-scale feature and turn it off again when not required. This gives a business the right of selection of services for which they decide to pay.

3. Flexibility

During peak times, most business owners end up investing more money in resources they don’t need; simultaneously, increasing the upfront cost for any business owner. When using Amazon web services, it is easy to customize, upgrade, maintain and configure programs and software with flexibility.

Business owners can even scale the services that meet all their requirements, eliminating extra investment of time and money. Selection can be made from multiple applications, tools, database, language, script and operating systems, available with AWS.

4. Timeliness

While provisioning the server, any local company would take more than 48 hours to do so which is no less than a pain. But it is totally different with AWS; it takes minutes to provision the server and test it.

In fact, the use of Amazon Machine Images will enable the business to accept as much as connections it wants, within a short span of time. The service is very ideal for the situation when a business is running its promotional campaign and accepting a lot of traffic to hit it websites in a fraction of seconds.

5. Try for free

In general, services which are simple to use and offer affordability at the same time are very much preferred. But again, just because something has affordability and availability, these do not simply make it a better option.

Amazon Web Services (AWS) is familiar with this concept. It offers the opportunity to register for free and use the services, at least for one year. Only a few months will be enough to understand the importance of buying the paid services, though!!

Some additional benefits are

• 5 GB storage capacity
• 24x7x365 customer support center
• Public forums
• Guidelines, documents and papers
• Elastic compute cloud system, including 750 hours usage monthly for Linux and Windows OS.

With Amazon Web Services, it is certain that your business has a lot to gain. Embrace this cutting edge on-demand cloud computing platform and get a performance powerhouse to deliver value for your business.

Cognitive Computing Trends

What exactly do you think as a human’s greatest possible skill? Solving problems is the greatest gift of God to the mankind because that brings us where we are today. Just a few decades ago when the revolutionary computers were introduced into the world, no one would have anticipated the machine to be solving our problems for us, only much better and with greater patience level.

Just as we’d have expected, we are advancing into the future faster than we invent all that we see today. The same is the case with C3PO which will be less to be seen in the future; that blessed us with Star Wars and Hal. The future, as we see it now, will be more about Cognitive Technologies, which comes with a greater ability to improve business management and the human-machine interaction.

How cognitive computing adds business value?

It is still a while before we put our best foot forward into the world of cognitive technologies, however, the value derived from cognitive computing cannot be disputed. Let us read the most probable changes it should bring to the business.

1. Increased productivity and better performance: With an impressive 360-degree view of financial and economic data for all the perspectives of a business, a better decision-making and forecasting is promised. Everything will be automated, including manufacturing, health diagnosis, failure detections in machines and lot more. Hence, the organizations embracing this change will definitely be more operational than before.
2. Improved customer experience: Just imagine the future of customer service with cognitive technology; a smart and customized service adapted by the preference of a customer would be a total win-win situation. An improved customer service means a leap in the number of customers, thus, a better and increased business. The cognitive technology also promises you to offer your customer a better buying experience. This will most probably be done by an analysis performed on the buyer’s personality by connecting with their social media profile.
3. Empowering employees with cognitive computing: If an organization has highly skilled professionals, then cognitive technology can help the organization to get best out of those skilled employees. As a skilled person can learn and grow simultaneously, the implementation of cognitive ecology will certainly help in achieving the task.
4. Consistent Analysis for the positive aspect of Business: With the implementation of cognitive technologies, the respective leaders can unfold a majority of their strategies to increase their business. With an effective level of accurate predictions, less number of untapped markets, and increase in product predictions, the business administration will work affluently than ever before.

The fascination for a better and an advanced future has greatly influenced lives around us. It is difficult to tell whether we are faster or still slower than what the previous generation might have imagined the life for the future. However, one thing is quite certain from the recent advancements – we are surely, entering another revolutionary era in human history. And cognitive computing is emerging as one of the biggest drivers of this change.

The Language Battle

Java and Python are two of most popular and powerful programming languages of present time. Beginner programmers are often confused about choosing the right one. Since we are a premier Java developing firm, our opinion is slightly leaned towards Java.

Although, hey! We love python too.

Java VS Python: Key Differences

• Braces vs Indentation
  • Python uses indentation to separate code into blocks. Java, like most other languages, uses curly braces to define the beginning and end of each function and class definition.
• Dynamic vs Static Typing
  • Java forces you to define the type of a variable when you first declare it and will not allow you to change the type later in the program. While Python uses dynamic typing, which allows you to change the type of a variable.
• Portability
  • Any computer or mobile device that is able to run the Java virtual machine can run a Java application, whereas to run Python programs you need a compiler that can turn Python code into code that your particular operating system can understand.
• Ease of use
  • Python is an easier language for novice programmers to learn. You will progress faster if you are learning Python as a first language than Java. However, the popularity of Java means that learning this powerful language is essential if you want your apps run everywhere.

Why People Choose Java

1. The strong java community

No matter how good a language is, it wouldn’t survive if there is no community to support. Java has a strong community who is ready to help throughout your career. I think its the reason why stackoverflow has the largest number of answers on java.

2. Java is free

If a programmer wants to learn a new language or an organization wants to use a technology, cost matters. This is why java achieved much popularity.

3. Huge collection of OpenSource libraries

Java is backed with a number of open source libraries that helps the developers to reduce their development time as well the lines of code. Some of these libraries are

• Apache Commons
• Google Guava
• JUnit
• SLF4J and Log4j

4. Powerful development tools

One can choose from several of the Development tools (IDE) that are available for java.

• Eclipse
• Netbeans
• IntelliJ IDEA
• jEdit
• JDeveloper

5. Java is platform independent

The main reason of Java’s popularity in the 1990s was the idea of platform independence.  Its tagline “write once run anywhere” attracted many developments into java. Most of the Java applications are developed in Windows environment and run in UNIX platform.

6. Java is Object Oriented and even supports functional programming with Java 8

Developing OOPS application is much easier, and it also helps to keep system modular, flexible and extensible.

The Python Advantage 

1. Python requires no “set up.” A full python environment is already on every Linux machine, and on Macs. On Linux, the program yum, or the Yellowdog Updater, Modified is written in python, so python is here to stay. Java requires a substantial amount of setup. So if you want to get started with python programming, just type python at the prompt. To start with Java, call someone who knows it.

2. The systems written in Java that we have purchased all suffer from the need to have particular versions of Java installed, and thick clients of these systems also have that requirement. Support of Java appears to be expensive. We do not yet have a similar number of python systems, but no one is expecting configuration management to be an issue with them. From an educational standpoint, this sounds like a good way to become frustrated.

3. Python has its own idiosyncrasies. In Java, every object must be a representation of some class, but in python the “variables” are of a unique flavor. Variables do not represent objects [cf. object: something in memory that has an address] nor are they pointers, nor are they references. It is best to think of them as temporary “names” for an underlying reality, much like the Allegory of the Cave in The Republic (Plato). From a learning standpoint, this may be more difficult for those of us with 35 years of experience than it is for those first taking up programming.

4. A number of companies are stuck with a great deal of legacy code written in Python 2. Consequently, Python suffers from a misconception about how strict or loose the typing system may be, and how strictly it may be enforced. Keep in mind that because Python mainly works with “names” of objects, we are really not discussing the same thing when we discuss types of Python’s objects that we are discussing in other languages. Python does offer some rather seamless type conversions that can make it seem that the concept of types is less strict than it is in fact. Learning Python 3 first makes sense, but most of the employment is still in Python

5. Compared with Java, python is terse. Personally, the growing amount of arthritis in our hands welcomes this feature. In truth, my C++ code was frequently criticized for its overuse of operator overloading and the ternary operator. This may not make it a good learning experience, because for many people learning comes more easily when the material is spelt out.

Our Advice

If you have to absolutely choose only one of the two and are not from computer science stream, definitely Python and if you are from computer science stream, Java. If no restriction, choose both.

Couchbase Vs MongoDb

Both Couchbase and MongoDB are document oriented databases which carry a document for their storage unit. It is not unknown fact that data rules pretty much in all that we do today. Everything is witnessed and stored in documents, both online and offline, soft copy and hard copy. And now we need some tools those are essential for the management of the data. This is where NoSQL database comes in to act as a backbone for taming the data.

With an increase in the use of technology, the demands for more facility increases, compelling every business to meet customer satisfaction. So, for the businesses dealing with data storage and its management, CouchBase and MongoDB are two of highly sought-after database service providers.

A comparison between the two is much needed for a better insight on which one to use for the greater benefit as a whole.

1. Fragmentation

Couchbase: Couchbase server breaks the data to count it horizontally. It first spreads out the hash space to all the server in the community formed by the clustering of data. The placing of hash is later used to count it, which is determined by the key available in each document.

MongoDB: MongoDB uses the fragmenting method as it is entirely a document-based data model. Its key will lead you to the exact location of the document in the web of documents.  The difference here is that, MongoDB gives you the free will of choice for placing the fragment key; whereas, the Couchbase does the entire fragmenting itself without your intervention/choice.

Winner: – MongoDB

2. Performance

Couchbase: Very impressive to note is the simple architecture of Couchbase, which efficiently performs all the write operations when applied to a large number of data centers without any breakdown, whatsoever. This directly shows its fluent performance and minimized or rare cases for inactivity.

MongoDB: Due to its architecture, sadly, MongoDB fails to meet your business expectation of assessing the workload when a large number of data centers are applied.

Winner: Couchbase

3. External Cache

Couchbase: Couchbase is completely incorporated and organized within itself. It raises no action for the use of an external cache, at all. Its application is really easy to execute and has no complexities with multi-parts. A user can never lose his path somewhere between learning the adjustments!

MongoDB: MongoDB which cannot serve concurrent customers in its list of services, does need to add an external cache for assistance to serve the users. This not only costs more money but even raises complications while working. MongoDB needs a lot of physical attention of its user, as well as a number of needful added arrangements.

Winner: Couchbase

From the above given comparison, it is evident to see that Couchbase narrowly edges MongoDB and comes out a winner of this comparison. It is hard not to appreciate the user-friendly built and easy to execute usage of it. Couchbase, for its simple format and subtle structure, is easy to deploy because tasks like installation, configuration, and records management pretty simplified.

Fraud Detection Trends in 2017

Before we welcome the hysterical upheavals of 2018, let us look back at some of the trending online scandals that have created a turmoil in the online market. Unsurprisingly, 2017 was yet another year filled with eerie and troublesome e-commerce and online frauds.  Thus, before you go ahead to start your own retail online business, read on to prepare for self-prevention against potential frauds coming your way.

This post will discuss the frauds and then their detection trend one at a time.

Fraud 1: Cross-border frauds

Now, the major growth is happening overseas, especially in Asia, which is also a hub for most of the online frauds. Retailers all around the globe are looking ahead to capitalize their boundaries towards Asia for its growing market. Yet, they will have to take care of rise in cross-border frauds, which again is a Red Cross sign for keeping check.

Trend 1: Remove fraud filters

According to a fraud survey, most of the internationally available merchants rely on Address Verification System (AVS) for order validation, which proved more or less redundant for validation anymore. Therefore, retailers are not much relying on AVS. About 70% of the merchants have set their own rules for international orders, such as, limited payment methods and banned IP addresses from several countries.

Fraud 2: Clean fraud

A criminal mind usually moves two-steps ahead. Privileges of the smarter technology, fraudsters now have more refined methodologies allowing the most sophisticated fraud, popularly termed as, Clean Fraud. In this phenomenon, it is not possible to know until before a chargeback is incurred.

Trend 2: Crosschecking the shopper’s transactions

This means a regular and consistent crosschecking of previous transactions to the ongoing ones. Look for repeated orders; it will help you to identify die-hard shoppers and distinguish the swindlers.

Fraud 3: Fraudsters as a disguise of mobile shoppers

With growing technology, shoppers are moving from desktops to mobile phones. In Japan, 50% sale is marked by mCommerce that included fraudsters as well. Therefore, to avoid this, retailers have to be very vigilant.

Trend 3: Tracking frauds by approval rates

Merchants are worried about frauds via mobile shopping and need something very secure to avoid it. The safest way is to track the CNP frauds, keep a check on order approval with a particular shopper. The social apps, GPS location, basic details will definitely help in identifying the fraudster.

Fraud 4: Omni-Channel exodus

Omni channel is spread all across the web, attached to every prestigious brand and pundit thinking. As many would say, it means ‘cross channel being done just well’. This means creating a website and mobile application to give the customer in-store and a better customer experience. However, sometimes a fraudster takes the place of genuine buyer and intervene in customer’s satisfaction.

Trend 4: Synchronize data to personalize the shopping experience

The entire concept of identifying a fraudster from a genuine customer is – to first understanding your customer. An Omni-channel provides you with information, which is required to have a good customer-retailer relation. It is well suited to keep a track of a customer’s entire history, which can leverage the geographic locations, demographic trends, etc., which are necessary to know that your customer is not a fraudster.

While one cannot stop digital frauds completely in e-commerce, methods like these can help in preventing them for sure.

The Amazing Cassandra

The Apache Cassandra- an open source distributed database has been a much-anticipated topic of debate, lately. It is a prime choice for the significant amount of App development and data management companies, working at fresh new start-ups and traditional legendary enterprises. It has become remarkably easy to perform the complete transition of a traditional database to an open source database since NoSQL took a leap by introducing the Apache Cassandra.

With a unique yet considerably efficient ability to offer a real-life performance and experience, Cassandra has been making the life of companies in web developments, software engineering, and Data analysis easy. No wonder why back in 2008 Prashant Malik and Avinash Lakshman initially originated the Cassandra at Facebook!

How Cassandra benefits businesses?

With an increasing number of businesses opting for the Apache Cassandra, let us have a brief at it advantages for a growing business.

1 – Elastic Scalability

Many say that elastic scalability is the biggest advantage of using the Apache Cassandra. As we have read above, as number of servers can be added, therefore, the now formed Cassandra cluster can be scaled up and down as you please without much hassle, i.e. without any downtime or pause occurring to the applications.

2 – Open Source

We have been hearing a lot about Apache Cassandra offering an Open Source service. What exactly does it mean? Being open source means- it is available to businesses for FREE! Yes, you read that right; you can download it without giving much thought to your pocket. It is not the end of the awesomeness that open sourcing offers, it has a huge Cassandra community where niche-specific people can come together and discuss various aspects of this huge open source projects. It is even compatible to be used with other Apache projects.

3 – Peer to Peer Architecture

Unlike a master-slave form of working, the Apache Cassandra follows a peer-to-peer architecture for execution, thus, resulting in rare chances for failure. This makes it possible to add as many servers as your business wants in data centers to make a Cassandra cluster. It means that all the servers are at the same level and any machine can answer the request from a client.

4 – Fault Tolerance

Usually, what worries any business the most is whether or not the stored data is safe? Well, Apache Cassandra not only secures the data but stores it at multiple locations. Even if one server fails, or someone hacks it, the user is able to retrieve the data with utmost ease from another location. It is up to your choice how many replications you want to create which is then activated by the high-level backup and recovery competencies of Cassandra.

5 – Great Analytics possibilities

There are 4 key methods of carrying out analytics on Cassandra

1. Solr based integrated search
2. Batch analytics integrating Hadoop with Cassandra
3. External batch analytics powered by Hadoop and Cloudera/Hortonworks
4. Spark based near real time analytics

This significantly expands the range and usage of analytics using Cassandra.

So, it is safe to say that Apache Cassandra is a total win-win situation for any organization using the solution. Be it high performance, predictable scaling, distributed database characteristic, or 100% uptime, Cassandra scores heavily on these parameters and emerges as the preferred open-source distributed NoSQL database management system.

Red Is Incredible

Redis is an in-memory key value datastore written in ANSI C programming language by Salvatore Sanfilippo.  Redis not only supports string datatype but it also supports list,  set, sorted sets, hashes datatypes, and provides a rich set of operations to work with these types. If you have worked with Memcached, an in-memory object caching system, you will find that it is very similar, but Redis is Memcached++.  Redis not only supports rich datatypes, it also supports data replication and can save data on disk.  The key advantages of Redis are :

1. Exceptionally Fast : Redis is very fast and can perform about 110000 SETs per second, about 81000 GETs per second. You can use the redis-benchmark utility for doing the same on your machine.
2. Supports Rich data types : Redis natively supports most of the datatypes that most developers already know like list, set, sorted set, hashes. This makes it very easy to solve a variety of problems because we know which problem can be handled better by which data type.
3. Operations are atomic : All the Redis operations are atomic, which ensures that if two clients concurrently access Redis server will get the updated value.
4. MultiUtility Tool : Redis is a multi utility tool and can be used in a number of usecases like caching, messaging-queues (Redis natively supports Publish/ Subscribe ), any short lived data in your application like web application sessions, web page hit counts, etc.  There are a lot of people using Redis and they can be found at the owner website.

Here are a few things we suggest thinking about when you are utilising the superpowers of Redis.

• Choose consistent ways to name and prefix your keys.  Manage your namespace.
• Create a “registry” of key prefixes which maps each to your internal documents for those application which “own” them.
• For every class of data you put into your Redis infrastructure: design, implement and test the mechanisms for garbage collection and/or data migration to archival storage.
• Design, implement and test a sharding (consistent hashing) library before you’ve invested much into your application deployment and ensure that you keep a registry of “shards” replicated on each server.

Let us explain each of these points in brief.

You should assume, from the outset, that your Redis infrastructure will be a common resource used by a number of applications or separate modules.  You can have multiple databases on each server numbered 0 through 31 by default, though you can increase the number of these.  However, it’s best to assume that you’ll need to use key prefixes to avoid collisions among various different application/modules.

Consistent key prefixing & Managing your namespace:

Your applications/modules should provide the flexibility to change these key prefixes dynamically.  Be sure that all keys are synthesized from the application/module prefix concatenated with the key that you’re manipulating; make hard-coding of key strings verboten.

Registry: Document and Track your namespace

We suggest that you have certain key patterns (prefixes or glob patterns) as “reserved” on your Redis servers.  For example you can have __key_registry__ (similar to the Python reserved method/attribute names) as a hash of key prefixes to URLs into your wiki or Trac or whatever internal documentation site you use.  Thus you can perform housekeeping on your database contents and track down who/what is responsible for every key you find in any database.  Institute a policy that any key which doesn’t match any pattern in your registry can/will be summarily removed by your automated housekeeping.

Garbage Collection: 

In a persistent, shared, key/value store, and in the case of Redis, in particular the collection of garbage is probably the single major maintenance issue. 

So you need to consider how you’re going to select the data that needs to be migrated out of Redis perhaps into your SQL/RDBMS or into some other form of archival storage, and how you’re going to track and purge data which is out-of-date or useless. 

The obvious approaches involve the use of the EXPIRE or EXPIREAT features/commands.  This allows Redis to manage the garbage collection for you, either relative to your manipulation of any given key, or in terms of an absolute time specification.  The only trick about Redis expiration is that you must reset it every single time.

Sharding: 

Redis doesn’t provide sharding.  You should probably assume that you’ll grow beyond the capacity of a single Redis server. Slaves are for redundancy, not for scaling, though you can offload some read-only operations to slaves if you have some way to manage the data consistency, for example the ZSET of key/timestamp values describe for expiry can also be used for some offline bulk processing operations; also the pub/sub features can be used for the master to provide hints regarding the quiescence of selected keys/data.

So you should consider writing your own abstraction layer to provide sharding.  Basically imagine that you have implemented a consistent hashing method and you run every synthesized key through that before you use it.  While you only have a single Redis server then the hash to server mapping always ends up pointing to your only server.  Later if you need to add more servers then you can adjust the mapping so that half or a third of your keys resolve to your other  servers.  Of course you’ll want to implement this so that the failure on a primary server causes your library/service module to automatically retry on the secondary and possibly any tertiary server.   Depending on your application you might even have the tertiary attempts fetch certain types of data from an another data source entirely.

The Complexity Of Facebook

Lets describe a single event at Facebook, “Like & Share.” This is very simple functionality, whenever you see a beautiful chick you like her pic and share.

Let’s go technical here.

1. Design a thumb for a “Like” and also design a share button.
2. Every post should have like and share button in the bottom.
3. Whenever someone likes or share, notification should go to the owner of the post.
4. Whenever someone likes, the post should boost up to the all friend circle who follows you.
5. There should be a counter for number of likes and share.
6. Whoever likes and share, save that information.
7. Privacy setting should also be there, if someone doesn’t want likes from unknown, hide it.
8. If someone clicks “Like”, they shouldn’t like it more than once. But if they want to share they can share multiple times.
9. If someone clicks “Like”, turn that button into “Unlike”.
10. There should also a like button on comments but there shouldn’t be any share button.

Now, this is just a high level design of simple functionality of “Like and Share”, which may not cover all the test cases which is presently live at Facebook.

If I will go for a coding side only for “Like and Share” Then this answer will become the longest answer of Quora.

Now Let’s see interesting facts:

1. There are approx 42 functionalities/features at Facebook like connecting with friends to Live Streaming. Not to forget image detection algorithm to tag a friend.
2. What you see in today’s Facebook is not created in one day but an evolution of 13 years of continuous coding.
3. “TheFacebook” which was created by Mark Zuckerburg is not running from a dorm anymore.
4. Today it has 18,770 Employees (As of March, 2017), just to manage single website.
5. When Facebook was created it has one server at Mark’s dorm and It had 30,000 Servers in 2008 in just 4 years from its inception. It is very difficult to maintain one server, and when it comes to maintain these many servers, buddy the cost is beyond your imagination.
6. It’s security is invincible that world’s renowned and well known Hacker Group “Anonymous” tried to hack it. They failed miserably. Same group who is responsible for many hacking and leaking an information.
7. Facebook stores approximately 300 PETABYTES of user data on its servers. There are 1 million gigabytes in a petabyte. The entire written works of humankind, in every known language (including Latin and other historical languages) from the dawn of recorded history, would occupy approximately 50 petabytes. Think about that for a minute. Can you handle the cost of these much storage devices?

The value of Facebook is NOT in the software. It is not in the design. The value of Facebook is in the billions of existing users. The value of Facebook is the brand that they have managed to build.

Sure, a programmer could create a website like Facebook. It might not scale initially, but as its user base grows, it could raise capital and hire engineers to make it scale. The patterns are established. It is not rocket science.

The same question applies to Google, don’t you think so ?

Well, it is not a matter of lack of human resource. A team can gather and develop it.

The real trick isn’t coding up another social media site.

The real trick is getting people to use it.

By their nature, such platforms they need a large user-base to work. and Facebook already dominates the social media space. Even Google was unable to unseat them. It’s not because google plus didn’t function.Its because they couldn’t steal away enough market share. The nature of their product makes it hard for someone else to come along and usurp them.