 So this module talks about MongoDB, of course it doesn't cover at all completely MongoDB, it just mentions certain features of MongoDB, what is covered with reference to the cloud, with reference to the facilities, with reference to the indexing. When we talk of the no SQL model, the what comes to anybody's mind is MongoDB. So MongoDB is kind of a poster child of no SQL. Now this is good for MongoDB, because MongoDB incorporated was earlier 10 gen, so it becomes synonymous in people's mind as people perceive that no SQL synonymous with MongoDB. Now it has its flip side also. The flip side is that when people go for MongoDB, they try to do things with MongoDB for which it was, it is not developed. They try to implement the relational model on MongoDB, which of course it is, which is, which is not its strength. It's not the purpose of MongoDB. MongoDB is no SQL. And in module number 152, I will describe the differences between MongoDB, vis-a-vis no SQL and my SQL. So they're different things. One is relational, there is non-relational. So that is the flip side. Now look at the module coverage. So we will look at the JSON documents and language, effectively indexing. This is something very powerful feature of MongoDB, which is, which is not there in other databases, which support indexing, of course, all support indexing and the MongoDB in the cloud that we will cover. And of course, the licensing advanced features, you can download MongoDB from the net for free, but it will not have certain features which are mostly desired by enterprises. So let's look at this module in more detail. So JSON is a JavaScript object notation. And this is a standard format for exchanging data. Okay. And it is popular and it is being used. And it's binary version. Bison. Okay. Binary JSON is, is supported, is produced, is offered by MongoDB. Why? Because it reduces the processing time. It gives good performance. That is one reason. Now other is that there are many languages, many, many languages, which are supported by MongoDB. And we have about like at the time of giving and recording this lecture, there are about 10 languages which are officially supported by MongoDB. These are those 10 languages. And there is a host of about more than 25. Some people call it 30 and more than 30 languages, which are unofficially supported by MongoDB. And these are those 25 plus unofficially supported MongoDB languages. So that, that, that is another reason about the popularity of MongoDB. Now let's talk about indexing. Now any database, as a matter of fact, any and every database can store data. That is the purpose of a database. Now storing the data in a database is one thing and retrieving it quickly, effectively, that is something very different. Now in traditional databases, when I say traditional database, it means the relational database. In the relational database model, we are using the concept of the primary key. So the primary key is the unique key. So basically used based upon the primary key, we can, every record is uniquely identified. And using this primary key, I can fetch that record. But that kind of record primary key concept works in say, for example, financial environment, in inventory, in a school university. But there are a host of other applications where these concepts don't work directly. If say, for example, I am looking for Haleem. I am looking for Haleem and I would like to search for it. I would like to search for it. And how would I know that which recipe is good? I would look for the comments. I am looking for the comments, searching for the comments. So for that, I need MongoDB provides a secondary index. Secondary index I can search and I will get the feedback about Haleem. Now the thing is that I am not satisfied with only that feedback. I would like to know that which recipes of Haleem are using red meat, are using red meat. And also less cholesterol, less cholesterol also. So I am looking at multiple things. And I may be and more than, this is not two, it can be more than two also. So I am looking at multiple fields. And then I can find what I'm looking for. Now there is a flip side also. The flip side also that if there are, if I categorize the comments into four categories or five categories, they are different combinations of comments. First and or there are different combination of the fields. For example, if there are four fields, say for example, if there are four fields, so maybe I'm looking at field one, two, or maybe three, four, or maybe one, two, four, or maybe whatever. So there is a large number of possible compound indexes. This is the flip side of the compound index. What is the solution is the solution is that there's an intersection of indices, intersection of indices, which is shown over here also. Okay. And that does not need a compound index, you don't need a compound index. And that reduces the disk and memory space also. Because you see with this, I need lots and lots of combinations. So for example, I have this indexes for the color over here, for the red color for the blue color. And this is for the product over here also for product. And I can use an intersection of these indices and get what I'm looking for with reduced disk space. Okay, so that is the advantage. So MongoDB in the cloud. Now MongoDB has many cloud platforms, which support MongoDB. And the reason is obvious, because TenGen company was this was is is a cloud based company. And of course, you can also have and host MongoDB on your private cloud also. There's a lot of flexibility of hosting MongoDB. And finally, what you get what you pay for. So if you're looking for advanced features, you can download MongoDB for free. But if you're looking for advanced features, which of course come at a premium, okay, then of course, you have to pay that premium. What you pay is what you get. For example, if you need the MongoDB management services, which can take care of disaster recovery, which is critical for a for an enterprise, you pay for it. Okay, security integrations, enterprise software integration, you integrate MongoDB with the software which is there. And of course, certified operating system for checking for for fault tolerance also for authentication also, and on demand training support commercial licenses. So you can you can have your MongoDB embedded in your in your commercial enterprise in your commercial applications. For that, you need license, you have to pay for it. So you as a chief information officer, which you will become one day, then you should be aware of the total cost of ownership, total cost of ownership as a CIO, you should know all those things. So you have to take care of all the things, look ahead and be aware of where you are stepping. That's all I have for this module. Thank you very