Creating, Using and Managing Text Indexes in MongoDB
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Creating, Using and Managing Text Indexes in MongoDB

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MongoDB Compass Database Visualizer For MongoDB Server
MongoDB Compass Database Visualizer For MongoDB Server
MongoDB Compass allows you to make smarter decisions about document structure, querying, indexing, document validation, and more. MongoDB Compass is available as part of subscriptions. This version is a free tool for development with MongoDB and includes a subset of the features of the app. The Community Edition is freely available to all users.
It allows you to analyze and understand the…
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MongoDB Indexes - What, How and the Data Structure behind the same?
Welcome to the MongoDB Video Series. In this video, I'm talking about MongoDB indexes. Indexes drastically impacts the performance of MongoDB especially the search queries It's highly unlikely that you can use MongoDB in production without MongoDB indexes In this video, I've created our own data and then apply mongodb indexes into them to see the performance difference. Not only that, I've also visually explained the B-Tree data structures which is used while creating MongoDB index Hope it help you to learn something new. Thanks for tuning in and watching #Mongodb #NoSQL #javascript #nodejs #js #mongodb compass #mongodbatlaa #mongoshell #node
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MongoDB in Real World Businesses
There was a time when it took months for planning out an application and its schema but the time has changed now. Especially in this age of big data, constant iteration of our application plays a critical role in satisfying customers. MongoDB enables such iteration. MongoDB data model makes it easy to do such iterations. So developers can easily evolve there applications and the schema follows.
These unique features make MongoDB a very popular database. Because of these features many industries have shifted towards MongoDB and have developed application which were never possible before.
Here are some case studies showing the charisma of MongoDB in some real world businesses
MetLife is among the largest insurance companies in the world. They wanted to harness there Big Data to create a 360- degree view of its customers so that they could know and interact with its more than 100 million clients as an individual. They spent many years trying to develop a centralized system using relational database but were unsuccessful.
Finally MetLife turned to MongoDB. With MongoDB over just 2 weeks they created a working prototype of a new system and just three months later, they finished a new version of this new system, called “MetLife Wall”.
How MongoDB helped?
MongoDB had this power of the flexible data model. With MongoDB it was easy to evolve schemas in real-time. It stores data in documents therefore managing customer data becomes easy. It can also handle the Big Data quite efficiently with auto sharding and it is also very flexible.
John Bunger, Senior architect at MetLife Said,
“MongoDB helped us to deliver that 360 view of the customer in just 90 days. That was really ground breaking for MetLife, ground breaking for the insurance industry. And it really set an example of the company that we want to be recognized as.”
The weather channel is an American television channel, this channel broadcasts weather forecast, weather related news and analysis. They wanted to develop a mobile application where they could iterate more quickly with a scalable system.
How MongoDB Helped?
With MongoDB, high costs and flexibility was replaced with simplified scale and speed. The weather channel could now quickly distribute the weather alerts to all the subscribers in the affected geographic locations in real-time. The application was now handling more than two million requests per minute with the MongoDB’s capability of scaling out.
Luke Kolin, Vice president of architecture at The Weather Channel said:
“As we work with our user base to figure out killer feature, rapid innovation cycles with MongoDB are a real benefit.”
Expedia is an online travel company. Expedia wanted a new feature of scratchpad because it made the travel search process fast, easy and personalized.
How MongoDB helped?
With MongoDB’s flexible data model and simple horizontal scaling, the users were given a seamless hopping experience and its rich indexes powered analytics that made personalized suggestion to the users while shopping.
Prashanth kokati, senior software engineer at expedia said: “Without MongoDB, it would’ve taken a much bigger team to get the app live so quickly.”
MongoDB is a database that has brought a revolution in the market with its unique features making applications which were never possible before. Hence, all these case studies justifies its popularity.
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MongoDB Integration with Other languages
MongoDB Integration with Other languages
MongoDB is an open-source database, which is reliable, globally scalable and inexpensive to operate. MongoDB provides native drivers for all popular programming languages and frameworks to make development natural. A list of supported drivers include:
Java, .NET, Ruby, PHP, JavaScript, node.js, Python, Perl, PHP, Scala etc.
An application communicates with MongoDB by way of a client library, called a driver is used for interacting with MongoDB in a particular language. The popular MongoDB drivers and client libraries include:
PHPMoAdmin is MongoDB Administration tool for PHP built on a stripped down version of the Vork high-performance framework. It can help you discover the source of connection issues between PHP and MongoDB.
Mongobee is a java tool which can help you manage changes in your MongoDB database and keep them synchronized with your java application. It provides new approach for adding changes based on Java classes and methods with appropriate annotations.
PyMongo is a Python distribution containing tools for working with MongoDB. MongoVUE is a .NET Graphical User Interface that gives an elegant and highly usable interface for working with MongoDB.
Node.js Driver is the officially supported node.js driver for MongoDB. It is written in pure JavaScript and provides a native asynchronous Node.js interface to MongoDB.
MongoDB also supports some Third-party GUI tools like: Robomongo, Fang of Mongo, Mongo3, UMongo etc.
Robomongo is a shell-centric cross-platform open source MongoDB management tool. It embeds the same JavaScript engine that powers MongoDB’s mongo shells. Everything you can write in mongo shell, you can write in Robomongo. Robomongo provides you with syntax highlighting, auto-completion, different view modes (text, tree) & more. It has its own features like multiple shells and multiple results.
Fang of Mongo is a web-based User Interface built with Django and jQuery. UMongo is a cross-platfrom Management-GUI, implemented in java.
MongoDB can be used with many programming languages and development environments as we have discussed above. With MongoDB, you can build applications that were never possible with traditional relational databases, as with the advanced features it provides an extensive driver support with the programming languages.
Top 5 quotes of MongoDB and NoSQL Industry leaders
MongoDB is the most popular NoSQL next-generation database that already serves many Fortune 500 and Global 500 companies across financial, e-commerce, gaming, healthcare, education and science etc. MongoDB was developed by Dwight Merriman, Eliot Horowitz and Kevin P. Ryan. Eliot Horowitz is the founder and CTO of MongoDB Inc., and Dwight Merriman currently serves as the founder and chairman of MongoDB Inc.
“The development period for MongoDB 3.0 has been the most eventful of my entire career,” said Eliot Horowitz. As MongoDB 3.0 brings with it massive improvements to performance and scalability, enabled by comprehensive improvements in the storage layer and with much more features. Again he says that “Users love MongoDB because it offers the fastest time to value compared to any other DBMS technology”. “With 3.0, MongoDB’s performance, scalability, and manageability now set the standard for today’s most demanding applications. Moreover, with this release users can build applications that deliver between 7x and 10x greater write throughput, while using up to 80 percent less storage, and managing their operations with up to 95 percent less effort.” Eliot Horowitz says that NoSQL databases can handle unstructured data. For ex: “Suppose you want to have a media collection. A person wants to upload pictures, video and anything that pertains to him or her. One big problem is that photos have different attributes than videos. You want to be able to store everything in the same collection but have different indexes for videos and song titles and photos, each with different fields but everything mashed all together. That is a pretty typical use example for what NoSQL databases like MongoDB can do.” “In five short years, the MongoDB community has transformed the data management landscape, creating the first compelling alternative to 40 years of relational databases,” said Max Schireson, CEO of MongoDB. That means that MongoDB has gained high popularity in few years, among other NoSQL databases and the RDBMS systems. “The cost of managing traditional databases is high. Mistakes made during routine maintenance are responsible for 80 percent of application downtime,” said Dev Ittycheria, President and CEO of MongoDB Inc. As it is easy to maintain the MongoDB database, as compared to other Relations databases.
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