Resources

December 16, 2021

Advanced Querying: Beyond the Basics

11 AM ET In this webinar, we will show you how the aggregation framework allows you to model simple and then increasingly complex queries and aggregations against your datasets, allowing you to group, join, and run window functions across documents in your collections. Then we'll talk about indexes, and the things you should consider when indexing your collections. Finally, we'll introduce you to some fundamental data modeling patterns, giving you a solid starting point for learning to effectively model data in MongoDB. Don’t miss this opportunity to learn about advanced querying and get your questions answered. We look forward to seeing you there!

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December 10, 2021

MongoDB Atlas on Google Cloud eWorkshop (Hong Kong)

14:00 - 17:00 HKT, session will be delivered in Cantonese Join the MongoDB and Google Cloud teams for invited-only virtual hands-on training on December 10th! In this 3-hour eWorkshop, we will teach you how to use MongoDB Atlas 一 the most wanted, fully elastic, resilient, and secure cloud data platform 一 on Google Cloud to help you build better applications. Choosing MongoDB Atlas on Google Cloud not only ensures your databases run according to operational and security best practices, but it is also the best way to combine Google’s constant innovation with the best database for building modern applications in the cloud. Attendees will have the chance to win Apple Watch and MongoDB Swag Box! eWorkshop agenda : MongoDB technical overview Google Cloud overview CRUD operations hands-on Aggregation Framework hands-on Atlas Search hands-on Note: eWorkshop content is geared towards senior solution/technology architects and data engineers. (basic knowledge of MongoDB is a plus)

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Let’S Explain Aggregations

Gain a better understanding of how aggregations are optimized and executed in MongoDB — whether you are writing a new one or looking to tune something that is already in production. You will also learn tips and tricks to improve query performance. We'll cover: An overview on the structure of explain plans in MongoDB Various optimizations that MongoDB executes when parsing aggregation pipelines Best practices you can leverage to avoid commonly observed anti-patterns Additional tips & tricks to improve the query performance

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Extend Your Learning

Working with data doesn’t need to be hard. And with MongoDB, it isn't. Learn more about MongoDB Atlas , the multi-cloud application data platform, MongoDB Realm , a highly performant mobile database, and more! With an integrated suite of cloud database services that allow you to address a wide variety of use cases, from transactional to analytics, from search to data visualizations, MongoDB can accelerate and simplify how you build with data. Register here to receive access to a variety of resources covering topics including what's new in MongoDB 5.0 , the MongoDB Atlas Data API Preview , transforming the customer experience with Atlas Search , and more!

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Purpose Built Optimizations for Time-Series Workloads in MongoDB 5.0

Time series data is generated everywhere-- from the heartbeat sensor in your smartwatch all the way to DevOps teams monitoring network traffic. However, you can face many challenges while building applications for time series data when using Relational and NoSQL databases. Both require manual schema optimization in order to provide high speed data ingestion, as well as custom ETL routines for archiving aged data. In MongoDB 5.0, all the hard work is done for you! During this 25-minute session, we’ll showcase some of the powerful and new native time series capabilities introduced in MongoDB 5.0. Through schema and indexing optimizations coupled with powerful new indexing and query functionality, you’ll learn how to build and run time series workloads faster, easier, and at a lower cost than ever before. Topics include: What is Time Series Data? The Challenges of Existing Time Series Solutions New Time Series Capabilities on MongoDB 5.0: Native Time Series Platform How to Use MongoDB’s Purpose Built Time Series Collections for your Applications

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Staying one step ahead of payments fraud with Featurespace and MongoDB

How money, data and fraud are three areas that are often intertwined Globally, payments fraud is constantly changing and evolving as consumers and businesses demand more digital experiences and payments services. With the number of transactions constantly rising, service providers must be able to determine if they are genuine and processed smoothly, while avoiding fraudulent ones. Preventative technology is key and constantly evolving, but so is fraud. A recent global survey conducted by Celent shows that 74% of corporates are willing to pay for improved security and fraud prevention. The payment service providers that succeed will be those that can stay one step ahead and protect their customers and stop fraudulent activity in its tracks. But how can this be achieved? In this on-demand webinar during International Fraud Awareness Week, we discussed: The state of the industry with emerging patterns and trends How organisations can overcome data silos and improve speed to action with data all in one place to detect fraud How to bring fraud prevention to life with MongoDB and Featurespace Real-life case studies on fraud prevention implementations and achieving measurable results You will hear from: Boris Bialek , Global Head of Industry Solutions, MongoDB Sean Neary , Senior Product Officer, Featurespace By filling in this form, you are agreeing to MongoDB sharing your data with Featurespace who participated in this discussion.

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December 15, 2021

Best Practice of Deploying MongoDB on AWS Featuring SHOPLINE (APAC)

11:30 IST I 14:00 SGT Curious to learn best practices of deploying MongoDB Atlas on AWS? Join us for our upcoming webinar on December 15 to get an overview of how you can increase performance, availability, and security for all your MongoDB deployments on AWS. Additionally, Ronald Li, Engineering Director of SHOPLINE, will join us to share SHOPLINE’s experience with MongoDB Atlas on AWS and for an exclusive Q&A. You’ll learn why SHOPLINE chose MongoDB Atlas on AWS as the company shifted focus to modernization, event-driven architecture, and data-as-a-service -- a true digital transformation. There will be a live demo of how to set up an Atlas cluster with AWS, as well as the opportunity to get your questions answered by our team of experts from MongoDB and AWS. Webinar Speakers: Derrick Chua, Senior Solutions Architect, MongoDB Mingwei Leong, Senior Partner Solutions Architect, Amazon Web Services Ronald Li, Engineering Director of SHOPLINE

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How to Rapidly Build a Globally Scalable & Secured SaaS Platform

Join this recorded Tech Talk as we sit down with Sanjay Garje, Co-Founder and CTO of Ribbon, the company behind the hybrid trade show SaaS platform that makes B2B Commerce fun, simple, and accessible to everyone across the globe. Prior to Ribbon, at Amazon Web Services (AWS), Sanjay was a Global leader helping companies like Netflix, Intuit, GoDaddy with their journey to AWS Cloud. So when a seasoned Cloud technology leader like Sanjay decided to build his own technology SaaS platform, he chose MongoDB Atlas as the database engine. Why? Listen in as Sanjay shares his insights into: Leading a growing SaaS platform technology company Scaling the databases design strategy to meet global demand: Crawl, walk, run Delighting customers with the real-time business intelligence without costing an arm and a leg Making the switch from internally managing the database to a self-managed database Better alignment for Center for Internet Security (CIS v8) Data Protection and Recovery Controls

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Ecommerce at MACH Speed With MongoDB and Commercetools

Modernizing the ecommerce experience Global retail ecommerce sales have surged over the past 18 months. Up by over 25% in 2020, retail ecommerce sales are projected to grow a further 16.8% to $4.921 trillion in 2021. One major problem standing in the way for many retailers taking advantage of this opportunity is that their legacy ecommerce and technical infrastructure is not ready for this new reality. In order to provide the bare minimum consumers now expect and be ready for an omnichannel future, ecommerce infrastructure needs to embrace the following eight principles: Real-time customer engagement : creating real-time responses to behaviors Single view of customer engagement : breaking down data silos, reducing data duplication and increasing data consistency Omnichannel : retailers must offer a multi-channel or multi-device experience Mobile-first : ecommerce must be mobile by default Dynamic product catalog : all in real-time Inventory verification and order management : all in real-time Scalability : infrastructures must be ready for sudden spikes in demand Flexibility : the ability to store data together to achieve real-time reactions Download this paper to learn how MongoDB and Commercetools make the above possible with the MACH approach (microservices, API-first, cloud-native SaaS, and headless) to architecting modern ecommerce solutions.

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