An Explanation of MongoDB Atlas' Features and Functionalities

hey everyone my name is Anaya riceingani from mongodb and I'm here today to discuss all things mongodb Atlas which is mongodb's fully managed Cloud database this means Atlas is the best database to handle various complexities that arise with deploying and managing all mongodb database deployments in the cloud for those who want to hit the ground running and incorporate a database into their Project without wanting to deal with all of the infrastructure resources and time that is normally needed with dealing with on-premise or self-managed database instances or clusters mongodb Atlas is the perfect solution with Atlas it is possible to spin up a cluster in minutes and it allows for flexibility so you can truly make your project yours first things first we're going to hit this button right here build the database and there are three types to choose from depending on your database needs serverless dedicated and shared through these options vary in price with the shared type being completely free Atlas also incorporates a pay as you go serverless model where billing is per views and you can pause or terminate your cluster at any time other options are flat rate per cluster type meaning you can customize exactly which to use depending on your needs Atlas allows you to choose exactly which cloud provider is perfect for you between Amazon web services Google Cloud platform and Microsoft Azure you have a variety of options to personalize and scale your cluster allowing for multi-cloud and multi-region data Administration enables you to expand Global coverage increase fault tolerance and even adhere to data compliance requirements for our demo we are going to be using an M20 dedicated cluster to show you all of the various services that are available in our Advanced option there are certain functionalities that exist in M20 clusters and above and we are going to explore these functionalities in this video to get an M20 cluster up and running on your Atlas account click create a dedicated cluster keep the default settings the same for now scroll all the way down and hit create cluster when you're setting up your database you can even manage your database users choose what database or collections your team members have access to you can set your username and your password and then hit create user to make sure that only you or the people you want have access to your cluster for additional security with Atlas you can configure private network access with private endpoints to your applications that connect with your database so you can be guaranteed that your data is secure for now I'm just going to click add my current IP address to make sure that my address can access my cluster once you're done with your security hit finish and close below now your cluster is ready to be deployed you should see this page come up on your Atlas account and as you can see new clusters take about seven to ten minutes to provision while we are waiting for our cluster to be up and running I'm going to walk you through some of the advanced security that we have available for your Alice account we are going to start with database access in database access you can remove or add any users you want who can have access to your database see here I can remove myself if I want by hitting delete or I can edit my username or my password I can even add a new database user if I want to not everyone needs to have the same access permissions to your cluster to create specific roles hit the custom roles tab in network access you can add or remove IP addresses that can connect to your cluster this is a great way to keep your cluster safe you can even include more advanced authentication processes by using the advanced tab under the security group now as we can see our cluster has been provisioned for the purpose of this video we are going to add in a sample data set provided by mongodb to do this press the ellipses menu and then click load sample data set once your sample data set has been successfully loaded in you will get this little notification at the top and this means that we can now connect to our database there are a variety of ways to connect to your database once it's up and running to connect to your cluster simply hit the connect button as you can see here you can connect with the mongodb shell you can connect using one of mongodb's native drivers we have python node.js Java go and so many more you can connect with mongodb compass which is a graphical user interface used to query Aggregate and analyze your data in a visual environment you can connect using vs code or you can even connect with the business intelligence tool once you have your cluster up and ready to go you can actually see how it's performing so let's hit the view monitoring tab from here you'll be taken to the metrics Tab and it has various database metrics such as cache activity and data utilization that can actually help you ensure your application is running the way it should be this tab is the perfect place to see where things are going wrong if they do go wrong Atlas also has a real-time tab that helps you see real-time performance in your cluster this tab can help you troubleshoot usage spikes or queries taking excessive amounts of time in your database the profiler tab is where you can analyze performance from your cluster this is a way to dig deeper into areas that could benefit from a performance optimization as you can see here only slow operations will be shown there is also the performance advisor tab that helps you to automatically analyze your cluster and provide recommendations on where to improve your performance you can create indexes improve schemas and drop indexes all through recommendations that directly come from Atlas the backup tab is where you're able to see when your data has been backed up along with the online archive tab which allows you to automatically archive any data you want according to your specific archiving rule so you can free up storage and resources on your cluster at a reduced cost the collections tab is really important because it helps you to visualize the data in your database I've already uploaded some sample data to this cluster as you saw earlier and so it has some Airbnb data some movie data Etc let's together see how I can fully utilize this tab I'm going to go down to the sample mflix comments and as you can see this has a variety of documents in our collection with various comments from different people I want to include my own document that has my name and my email address so I can go over here and click insert document the ID is already given for you every single document in a collection needs to have a unique ID but I'm going to add my name right here which is Anaya raisingani I'm going to add a new field and include my email which is going to be example at mongodb.com and now I'm going to insert this new document into my collection so just hit the insert button and it's been inserted but let's see how we can check to see if it's inserted so now let's filter through the documents and use mongodb's Query language to parse through the documents and return the document that I just included so we are going to do the field which is name and we're only going to do the name fields for now to see if that returns the document we want and as we can see here it does now that we have our document in front of us let's say that I want to remove my last name we can edit that really easily by just clicking edit document going over here and removing my last name now I want to update the document I'm just going to hit the update button and as we can see the filter no longer applies because the filter has to be exact so now if I put my entire name in Ira singhani it doesn't show up but if I remove my last name my document shows up again while we're in the collections tab I want to show you guys something else that is really cool it is the aggregation pipeline so the aggregation pipeline builder in Atlas is unique because it allows you to create and test each separate stage of your aggregation pipeline this really allows for ease of use and it helps make complex aggregations a little more digestible I am going to show you guys an aggregation example using our sample restaurants cluster and using our restaurants database so now that we have that up and running we're going to start building up our aggregation pipeline first things first I'm going to add my first stage I'm going to click dollar sign match so this match stage is the same filter search that I did with my name and as you can see let's say that I want to match a sample set of 10 documents that are all located in the borough of Brooklyn I can do that by typing in burrow and Brooklyn into my first stage and as you can see 10 documents show up that are all with restaurants that are located in Brooklyn so now let's add another stage let's say I want to limit the amount of sample documents shown and I only want two sample documents by doing this I can click add stage select the dollar sign limit operator and just provide a number of let's say five I want five documents cool and so five documents that are in the borough of Brooklyn have been also output here as you can see from these tabs above you can also create indexes directly in your database along with any schema suggestions or anti-patterns Atlas isn't just limited to managing your database there are a multitude of data services that you can use alongside mongodb Atlas the first being Atlas search Atlas search is an integrated fully managed search engine that automatically syncs to your database it is built on Apache leucine and completely removes the need for a separate search engine with search you can create search indexes construct natural language search queries and build queries using the dollar sign search aggregation pipeline operator app services are another great inclusion of Atlas they are fully managed back end services that allow you to build applications integrate various services and connect to and work with your cluster data faster these Services make it easy to run apps and back-end services on top of Atlas one example of app Services is the data API want to use HTTP requests to read and write data to your cluster Atlas has a data API feature that allows you to do this with just an https client and a valid API key the data API allows you to use all of the applicable crud create read update and delete operations and aggregate operations on your data you can use this API whenever you want to integrate your Atlas clusters with any applications that support HTTP requests what about if you want to visualize your data you can do this with mongodb charts chart is a way for you to get a look at your Atlas cluster data it is a powerful tool to help you get a clear understanding of your data while allowing you to pick up on patterns and correlations charts enables you to truly understand the bigger picture of your database some honorable mentions that I want to include in this video are triggers these are helpful because you can set a trigger to look for certain events such as inserts updates deletions Etc and respond automatically with server-side logic another honorable mention is data Federation it is a powerful inclusion in Atlas if you have multiple data sources you can query transform move and aggregate data across these data sources seamlessly it helps with data access for the user wherever this data might live hopefully now you all understand how powerful and useful mongodb Atlas really is get started today and test it out yourself with the free cluster for a more hands-on experience with our fully managed database as a service solution for more information on mongodb Atlas and how to use it please check out our documentation in the link below

Channel: MongoDB

Views: 7,257

Keywords: mongodb data api, mongodb, mongodb atlas, nosql, nosql database, serverless, what is nosql, crud, database, databases, nosql tutorial for beginners, nosql tutorial, mongodb university, mdb, mongodb atlas database, how to use mongodb atlas, app development, mobile database, using mongodb, what is mongodb, serverless database, nosql databases, AWS, mysql, app services, da

Id: HPwdm094Ukk

Length: 15min 2sec (902 seconds)

Published: Tue Nov 22 2022