News at MongoDB

All the news around MongoDB

Why I Wrote the New MongoDB Aggregations Book

In early May 2021, I published my book, Practical MongoDB Aggregations, which I released electronically and free for anyone to read . I love the MongoDB database and the uniqueness and power of its aggregation framework to analyse and manipulate massive amounts of data intuitively and efficiently. The opportunity to share this passion with others spurred me to write the book, with which I aim to support developers, architects, data analysts, data engineers, and data scientists to better understand how to maximise their productivity and effectiveness when building aggregation pipelines, as well as how to optimise these pipelines. Like many people over the past year during the pandemic, I’ve struggled to keep myself occupied when not busy doing my day job. Hence, my book was born not just from a desire to improve people’s knowledge but as my pandemic project, written over many weekends, to stave off the boredom. I believe aggregation pipelines provide a powerful domain-specific language for data processing in a way I’ve not seen before in other data-oriented tools, languages, or standards. SQL is a good data query language that caters to some analytical use cases via “group-by/having” statements. However, it typically has to be paired with a procedural language (e.g., Oracle’s PL/SQL ) to encompass an ordered set of complex data transformation rules. In the big data world of Hadoop , I find the MapReduce approach is too complex to develop with efficiently. Higher-level tools like Spark help alleviate some of this. However, by the necessity of still having to be general-purpose and versatile, the amount of Spark code required to process data sitting in any type of database is still too high for my liking. Many ETL tools provide proprietary data transformation capabilities, but these have to cater to the lowest common denominator capabilities across all the different types of databases they interact with. For these reasons and from experience, I consider MongoDB Aggregations to be the best tool for processing large data sets because it combines performance with productivity. Nevertheless, I sense the aggregation framework is shrouded in mystery for many people, hence my desire to demystify it with this book. I believe I identified a knowledge gap that many users wanted to be filled. MongoDB Inc. provides excellent reference documentation about aggregations in the MongoDB Manual , and MongoDB University provides a tremendous free online training course on aggregations . What I felt was still to be addressed was an opinionated yet informed perspective on how best to assemble aggregation pipelines from the well-documented parts—something that points the way to achieve optimal productivity and performance, accompanied by fully formed example pipelines to help put these approaches into practice. I hope readers of my book will learn some new things of value and enjoy reading it. A good test of the relevance of my book, in time, will be if people come back to it repeatedly as they continue with their journey of developing aggregations. Read the book for free now!

May 25, 2021
News

Introducing: Atlas Operator for Kubernetes

The MongoDB Enterprise Operator serves to automate and manage MongoDB clusters on self-managed infrastructure. While this integration has provided complete control over self-managed MongoDB deployments from a single Kubernetes control plane, we’re taking it a step further by extending this functionality to our fully-managed database—MongoDB Atlas. We’re excited to introduce the trial version of the Atlas Operator for Kubernetes. The Atlas Operator will allow you to manage all your MongoDB Atlas clusters without ever having to leave Kubernetes. Keep your workflow as seamless and optimized as possible by managing the lifecycle of your cloud-native applications from where you want most. With the trial version of this Atlas Operator, you can provision and deploy fully-managed MongoDB Atlas clusters on the cloud provider of your choice through Kubernetes. This provider is especially important for those seeking to unlock the power of multi-cloud with unique tools and services native to AWS, Google Cloud, and Azure without any added complexity to the data management experience. With this new Atlas Operator, you get the best of all clouds with multi-cloud clusters on Atlas , coupled with the freedom to run your entire stack anywhere, all while managed in one central location. The “trial version” simply means it has all the core functionality to provision fully-managed Atlas clusters, but the bells and whistles are yet to come. In addition to encapsulating core Atlas functionality, it ensures Kubernetes Secrets are created for each database user which allows for easier management of sensitive data. The Atlas Operator also allows you to create IP Bindings so your applications can securely access clusters. If you’re interested in using the trial version of the Atlas Operator today, follow our quickstart guide below to get started! Quickstart Below you’ll find the steps to create your first cluster in Atlas using the Atlas Operator. Note that you need to have a running Kubernetes cluster before deploying the Atlas Operator. Register/Login to Atlas and create API Keys for your Organization. This information together with the Organization ID will be used to configure the Atlas Operator access to Atlas. Deploy the Atlas Operator kubectl apply -f \ https://raw.githubusercontent.com/mongodb/mongodb-atlas-kubernetes/main/deploy/all-in-one.yaml Create a Secret containing connection information from step one. This Secret will be used by the Atlas Operator to connect to Atlas: kubectl create secret generic mongodb-atlas-operator-api-key \ --from-literal="orgId=<the_atlas_organization_id>" \ --from-literal="publicApiKey=<the_atlas_api_public_key>" \ --from-literal="privateApiKey=<the_atlas_api_private_key>" \ -n mongodb-atlas-system Create AtlasProject Custom Resource: cat <<EOF | kubectl apply -f - apiVersion: atlas.mongodb.com/v1 kind: AtlasProject metadata: name: my-project spec: name: Test Atlas Operator Project projectIpAccessList: - ipAddress: "0.0.0.0/0" comment: "Allowing access to database from everywhere (only for Demo!)" EOF Create AtlasCluster Custom Resource cat <<EOF | kubectl apply -f - apiVersion: atlas.mongodb.com/v1 kind: AtlasCluster metadata: name: my-atlas-cluster spec: name: "Test-cluster" projectRef: name: my-project providerSettings: instanceSizeName: M10 providerName: AWS regionName: US_EAST_1 EOF (You'll have to wait until the cluster is ready - "status" field shows "ready:true":) kubectl get atlasclusters my-atlas-cluster -o=jsonpath='{.status.conditions[?(@.type=="Ready")].status}' True Create a Secret for the password that will be used to log into Atlas Cluster Database kubectl create secret generic the-user-password \ --from-literal="password=P@@sword%" Create AtlasDatabaseUser Custom Resource (references the password Secret) cat <<EOF | kubectl apply -f - apiVersion: atlas.mongodb.com/v1 kind: AtlasDatabaseUser metadata: name: my-database-user spec: roles: - roleName: "readWriteAnyDatabase" databaseName: "admin" projectRef: name: my-project username: theuser passwordSecretRef: name: the-user-password EOF Shortly the Secret will be created by the Atlas Operator containing the data necessary to connect to the Atlas Cluster. You can mount it into your application Pod and read the connection strings from the file or from the environment variable. kubectl get secrets/test-atlas-operator-project-test-cluster-theuser \ -o=jsonpath="{.data.connectionString.standardSrv}} | base64 -d mongodb+srv://theuser:P%40%40sword%25@test-cluster.peqtm.mongodb.net Stay Tuned for More Be on the lookout for updates in future blog posts! The trial version of the MongoDB Atlas Operator is currently available on multiple marketplaces, but we’ll be looking to make enhancements in the near future. For more information, check out our MongoDB Atlas & Kubernetes GitHub page and our documentation .

April 8, 2021
News

Global, Multi-Cloud Security at Scale with MongoDB Atlas

In October 2020, we announced the general availability of multi-cloud clusters on MongoDB Atlas . Since then, we’ve made several key improvements that allow customers to take advantage of the full breadth of MongoDB Atlas ’ best-in-class data security and privacy capabilities across clouds on a global scale. Cross-Cloud Security with MongoDB Atlas A common question we get from customers about multi-cloud clusters is how security works. Each cloud provider offers protocols and controls to ensure that data within its ecosystem is securely stored and accessed. But what happens when your data is distributed across different clouds? Don’t worry–we have you covered. MongoDB Atlas is designed to ensure that our built-in best practices are enforced regardless of which cloud providers you choose to use, from dedicated network peering connections to customer-managed keys for data encryption-at-rest and client-side field-level encryption. Private Networking to Multiple Clouds You can now create multiple network peering connections and/or private endpoints for a multi-cloud cluster to access data securely within each cloud provider. For example, say your operational workload runs on Azure, but you want to set up analytics nodes in Google Cloud and AWS so you can compare the performance of Datalab and SageMaker for machine learning. You can set up network peering connections for all three cloud providers in Atlas to allow each of your cloud environments to access cluster data in their respective nodes using private networks. For more details, take a look at our documentation on network peering architecture . Integrate with Cloud KMS for Additional Control Over Encryption Any data stored in Atlas can be encrypted with an external key from AWS KMS, Google Cloud KMS, or Azure Key Vault for an extra layer of encryption on top of MongoDB’s built-in encrypted storage engine . You can also configure client-side field level encryption (client-side FLE) with any of the three cloud key management services to further protect sensitive data by encrypting document fields before it even leaves your application ( support for Azure Key Vault and Google Cloud KMS is available in beta with select drivers ). This means data remains encrypted even while it is in memory and in-use within your live database. Even though the data is encrypted, it remains queryable by the application but is inaccessible to any administrators running the database or underlying cloud infrastructure for you. Beyond security, client-side FLE is also a great way to comply with right to erasure requests that are part of modern privacy regulations such as the GDPR or the CCPA. You simply destroy the user’s encryption key and their PII is unreadable and irrecoverable in memory, on disk, in logs, and in backups. For multi-cloud clusters, this means you can take advantage of multiple layers of encryption that use keys from different clouds. For example, you can have PII data encrypted client-side with AWS KMS keys, then stored in both an AWS and Google Cloud region on Atlas and further encrypted at rest with a key managed via Azure Key Vault. Global, Multi-Cloud Clusters on MongoDB Atlas For workloads that reach users across continents, our customers leverage Global Clusters . This gives you the unique ability to shard clusters across geographic zones and pin documents to a specific zone. Now that Atlas is multi-cloud, you can now choose from the nearly 80 available regions across all three providers, expanding the potential reach of your client applications while making it easy to comply with data residency regulations. Consider a sample scenario where you’re based in the US and want to expand to reach audiences in Europe. To comply with GPDR , you must store EU customer data within that region. With Global Clusters, you can configure a multi-cloud cluster with a US zone and an EU zone. In the US, you choose to run on AWS, but in Europe, you decide to go with Azure because it has more available regions. All of this can be configured in minutes using the Atlas UI: simply define your zones and ensure that your documents contain a location field that dictates which zone they should be stored in. For more details, follow our tutorial for how to configure a multi-cloud Global Cluster on Atlas . Future-Proof Your Applications with Multi-Cloud Clusters There are many reasons why companies are considering a multi-cloud strategy , from cross-cloud resiliency to geographical reach to being able to leverage the latest tools and services on the market. With MongoDB Atlas, you get best-in-class data security and operations and intuitive admin controls, regardless of how many cloud providers you want to use. To learn more about how to deploy a multi-cloud cluster on MongoDB Atlas, check out our step-by-step tutorial , which includes best practices for node distribution, instructions for how to test failing over to another cloud, and more. Safe Harbor The development, release, and timing of any features or functionality described for our products remains at our sole discretion. This information is merely intended to outline our general product direction and it should not be relied on in making a purchasing decision nor is this a commitment, promise or legal obligation to deliver any material, code, or functionality.

April 7, 2021
News

MongoDB Launches Sales Academy

We’re thrilled to announce our inaugural MongoDB Sales Academy! This program will prepare emerging professionals with the training and experience they need to jumpstart a career in sales. We’re looking for recent college graduates with an interest in technology to join our rapidly growing sales team. “The creation of a program designed to develop recent college graduates into sales professionals is a natural extension of MongoDB’s culture of talent development. We have best in breed sales enablement and onboarding programs, and a “BDR to CRO” program focused on accelerating sales careers. We have an opportunity to bring these world-class training programs to those who are starting their careers, and to turn emerging professionals into future leaders at MongoDB.” - Meghan Gill, VP Sales Operations & SDR The Sales Academy will be a full time, paid 8-week training program based in Austin, TX. It will focus on training and developing future MongoDB Sales Development Representatives as, upon completion, these recent college graduates will move into a full time SDR position. Those who are part of the Sales Academy will have direct one-on-one support from their sales mentors, MongoDB’s leadership team, the Campus Team, and each other. These New Grads will complete a best-in-class training program, which includes both technical concepts and sales processes. Through regular coaching and professional development training, our Sales Academy New Grads will graduate from the program and become full-time members of the Sales team at MongoDB. “Life at MongoDB is ever-evolving and a great start for anyone looking to take their career to the next level. You can expect to constantly learn new things about technology and your customers, work alongside some of the best sales professionals in the industry, and to be on the forefront of innovation. If you want to understand technology like never before, work with customers modernizing today’s world, and get consistent feedback from peers and leadership, this is the right place for you.” - Maya Monico, SDR Manager This isn’t the first time that MongoDB has hired students into our sales organization. Hannah Branfman was part of our SDR Internship program and, upon graduating from her school, joined us full-time. When asked about what sales at MongoDB is like, Hannah says: “If you have ambition, are coachable and have a strong desire to learn, MongoDB will be a great fit for you. You have to be willing to make mistakes and remain naturally curious — don’t stop asking questions! If you have the perseverance to not only get here, but to then set the bar high for yourself and surpass it, you will fit in great. Get ready to make an impact!” - Hannah Branfman, SDR We’re eager to find recent college graduates who are ambitious and excited to learn. If you’re interested in kickstarting your sales career at MongoDB in our Austin office, this could be the perfect fit for you! The job post is now up and we look forward to reviewing your application and getting to know you!

February 3, 2021
News

MongoDB Realm Sync is GA

Every mobile developer wants to build an app that users will love - meaning you want to build apps that work for users regardless of signal strength, that react to changes in data in real time, and that won’t drain your user’s battery life or use excessive amounts of data. In June, we released MongoDB Realm , a set of integrated application development services that makes it possible for anyone to build a great app - whether you’re a solo developer working to stand up your idea, or part of a larger team shipping your latest release. As part of this, we announced a public beta for MongoDB Realm Sync , which makes it easier for you to keep data in sync across users, devices, and your back end, even when devices aren’t always online. We’re excited to share that as of today, Realm Sync is now Generally Available (GA). We believe Realm Sync offers a best-in-class solution for offline-first app developers, who need to move data between a local client and the cloud. With the Realm Sync service, we’ve significantly reduced the code you need to write, while also reducing the complexity of your app architecture. Crucially, we’ve done it while making sure everything is built to optimize for battery power, CPU, and bandwidth. As a developer, you no longer need to write (or maintain) thousands of lines of complex conflict resolution and networking code. Realm Sync handles that for you, making it simple to move data between the local Realm Mobile Database and MongoDB Atlas on the back end. You can build features faster, reduce bugs, deliver a better user experience – and do it all without having to worry about standing up or scaling servers. Download the MongoDB Realm Whitepaper Building for an Offline-First Environment To many development teams, synchronizing data between the client and your back end sounds simple. But when connectivity isn’t guaranteed, it becomes time-consuming and complex to achieve. MongoDB Realm simplifies data sync. Synchronization works bi-directionally, moving data between the Realm Mobile Database on the client-side and MongoDB Atlas on the back end. Automatic conflict resolution resolves any data conflicts that may emerge across multiple devices, users, and your back end, and ensures data is consistent whenever mobile devices come online. Because data is synced to Atlas, applications can easily scale up or down infrastructure as app usage changes. MongoDB Realm Sync also: Speeds feature innovation. Realm’s Mobile Database - used to store data locally on device, and MongoDB Realm Sync - both reduce the code developers need to write, and free up time to focus on building new features that provide unique business value. Works across platforms. Realm Mobile Database and MongoDB Realm Sync work on any platform, for any mobile device. Is secure and stable. MongoDB Realm lets you encrypt data in-flight or at-rest, both in the cloud and on-device. MongoDB Realm Sync in Action Fortune 500 businesses and cutting-edge start-ups are already using the Realm Mobile Database and MongoDB Realm Sync to build their apps today. Srikanth Gandra, Director of Digital Technology for 7-Eleven, built a mobile app on MongoDB Realm that’s been successfully rolled out for use across the United States and Canada. “What we’ve created is really innovative. Since rolling this out to all 8,500 stores in North America, we’ve been able to sync data across more than 20,000 devices on a nearly real-time basis," he said. "[Managers] can start using devices immediately, rather than waiting 2-3 minutes to download the data on initial startup, like they used to. Data accuracy - especially around inventory when sales happen or shipments arrive - has really improved.” “We’re evaluating using Realm and Realm Sync to assist with inbound and outbound parcel shipping use cases,” said James Fairweather, Chief Innovation Officer, Pitney Bowes. “As an example, we are exploring building an app on Realm for our front-line workers to scan a package that would automatically sync the data back to MongoDB Atlas providing consistent reporting and up-to-date logistics throughout the shipping journey.” With MongoDB Realm Sync, mobile developers have the tools to make data sync simple, making sure they both build apps fast, while still making sure that even complex components like real-time data sync are built right. Try MongoDB Realm Sync, and get started building your offline-first app. Try MongoDB Realm Sync Today

February 2, 2021
News

Learn How to Scale Your Startup with this Educational Series

As a startup, you're probably interested in spending more time on shipping features than managing your database. Upskill in the new year with Scaling Your Startup with MongoDB Atlas: A Series . Join us for a three-part educational monthly webinar series kicking off January 26, completely focused on how to do less with more. When? The last Tuesday of every month, January through March, at 9 am PT/noon ET What? Our technical experts will take you through NoSQL, the MongoDB Query Language, MongoDB Atlas (our global cloud database service), and show you how to take the heavy lifting out of database management. View Scaling Your Startup with MongoDB Altas: A Series Why NoSQL for Startups | Lauren Schaefer | January 26 Scale Your Startup with MongoDB Atlas | Mike Lynn | February 23 Reaching Scalability with MongoDB Atlas | Adrienne Tacke | March 30 Where? Zoom How much? Free! Who should attend? Attend if you are a MongoDB beginner, in need of a technical refresher, building a product or service, or part of a startup. Will it be recorded? Of course. Each webinar will be recorded and posted to the website for you to watch anytime, at your convenience. Why? Just check out the takeaways below. Plus at the end of each presentation, you’ll have time to submit queries for Q&A with the technical expert. Key takeaways will include: Mapping terms & concepts from tables to documents Discovering the 4 major advantages of documents for your startup Changing your mindset in 3 key ways Deploying a free tier cluster Adding users & managing user access Connecting to MongoDB Compass, the GUI for MongoDB What's Realm? Third-party integration What is and why Multi-Cloud? How to set-up Multi-Cloud Cluster And much more! Save Your Spot for Scaling Your Startup with MongoDB Atlas: A Series

January 13, 2021
News

MongoDB Atlas Online Archive for Data Tiering is now GA

We’re thrilled to announce that MongoDB Atlas Online Archive is now Generally Available. Online Archive allows you to seamlessly tier your data across Atlas clusters and fully managed cloud object stores, while retaining the ability to query it through a single endpoint. Reduce storage costs. Set the perfect price to performance ratio on your data. Automate data tiering. Eliminate the need to manually migrate or delete valuable data. Queryable archives. Easily federate queries across live and archival data using a unified connection string. With Online Archive, you can bring new use cases to MongoDB Atlas that were previously cost-prohibitive such as high volume time-series workloads, data archival for auditing purposes, historical log keeping and more. Manage your entire data lifecycle on MongoDB Atlas without replicating or migrating it across multiple systems. What is Atlas Online Archive? Online Archive is a fully managed data tiering solution that allows you to tier data across your "hot" database storage layer and "colder" cloud object storage to maintain queryability while optimizing on cost and performance. Online Archive is a good fit for many different use cases, including: Insert heavy workloads, where data is immutable and has lower performance requirements as it ages Historical log keeping and time-series datasets Storing valuable data that would have otherwise been deleted using TTL indexes We’ve received amazing feedback from the community over the past few months while the feature was in beta and we’re now confident in supporting your production workloads. Our users have put the feature through a variety of use cases in production and development workloads which has enabled us to make a wide range of improvements. Online Archive gives me the flexibility to store all of my data without incurring high costs, and feel safe that I won't lose it. It's the perfect solution. Ran Landau, CTO, Splitit Autonomous Archival Management It's easy to get started with Online Archive and it requires no ongoing maintenance once it’s been set up. In order to activate the feature, you can follow these simple steps: Navigate to the “Online Archive” tab on your cluster card and begin the setup flow. Set an archiving rule by selecting a date field, with dot-notation if it’s nested, or creating a custom filter. Choose commonly queried fields that you want your archival queries to be optimized for, with a few things in mind: Your data will always be “partitioned” by the date field in your archive, but can be partitioned by up to two additional fields as well. The fields that you most commonly query should be towards the top of the list (date can be moved to the top or bottom). Query fields should be chosen carefully as they cannot be changed after the fact and will have a large impact on query performance. Avoid choosing a field that has unique values as it will have negative performance impacts for queries that need to scan lots of data. And you’re done! MongoDB Atlas will automatically move data off of your cluster and into a more cost-effective storage layer that can still be queried with a single connection string that combines cluster and archive data, powered by Atlas Data Lake . What's Next? Along with announcing Online Archive as Generally Available, we’re excited to share a few additional product enhancements which should be available in the coming months: Private Link support when querying your archive Incremental deletes of data from your archive Support for BYO key encryption on your archival data Improved performance and stability Try Atlas Online Archive Online Archive allows you to right-size your Atlas clusters by storing hot data that is regularly accessed in live storage and moving colder data to a cheaper storage tier. Billing for this feature will include the cost to store data in our fully managed cloud object storage and usage based pricing for querying archive data. We can’t wait to see what new workloads you’ll bring onto MongoDB Atlas with the new flexibility provided by Online Archive! To get started, sign up for an Atlas account and deploy any dedicated cluster (M10 or higher). Have questions? Check out the documentation or head over to our community forums to get answers from fellow developers. And if we’re missing a feature you’d like to see, please let us know ! Safe Harbor Statement The development, release, and timing of any features or functionality described for MongoDB products remains at MongoDB's sole discretion. This information is merely intended to outline our general product direction and it should not be relied on in making a purchasing decision nor is this a commitment, promise or legal obligation to deliver any material, code, or functionality. Except as required by law, we undertake no obligation to update any forward-looking statements to reflect events or circumstances after the date of such statements.

November 30, 2020
News

Re-Imagining What A Cloud-Native Database Can Be

COVID-19 has compelled companies of all sizes and industries to reinvent themselves. From the way they work to the way they interact with customers, the pandemic has forced an urgent shift to a digital-by-default customer experience and, as a result, has accelerated the move to the cloud. But as companies make the move, many are finding that the same data silos and operational complexity that thwarted innovation for decades is simply following them into the cloud. Developers responsible for building today’s apps have to work with a patchwork of technologies, data models, APIs, and languages across disparate systems to deliver the right data at the right time to power critical applications and services. To better serve these developers, we’ve expanded our capabilities outside of the core database into a robust data platform we call MongoDB Cloud . At its core is MongoDB Atlas, our fully managed global cloud database, which enables your developer teams to spend less time on undifferentiated work and more time writing code that adds business value. By adding capabilities such as Atlas Search , Atlas Data Lake , MongoDB Charts and MongoDB Realm , which provide a consistent experience for working with data in different ways, you’re drastically reducing the cognitive burden on development teams. Simply put, MongoDB Cloud allows you to easily deploy, manage, and scale data architectures designed to support the converging requirements of transactional and analytical systems within a single elegant platform. Any cloud, anywhere, anytime The pandemic has put a spotlight on resilience and agility and showcased the importance a data platform can have for your business. This has not only accelerated the migration to the public cloud, but also the move to multi-cloud environments. Many of our customers rely on more than one cloud provider, and 55 percent of organizations currently report using multiple public clouds . That’s why we designed our offerings to have the same great developer experience regardless of which cloud provider or providers you use. Since launching in 2016, MongoDB Atlas has always pushed the boundaries of what’s possible in cloud data management, with customers able to deploy their data from more than 75 regions worldwide across AWS, Azure, and Google Cloud. And with the recent launch of multi-cloud clusters on MongoDB Atlas, we’ve recast the cloud and development experience again. With this first-of-a-kind capability, companies gain the ability to distribute their data in a single cluster across multiple public clouds simultaneously, or move workloads seamlessly between them. This is true data portability, enabling the freedom and flexibility to use best-of-breed services across multiple platforms, and ensuring cross-cloud resiliency. But we’re not standing still. Introducing Online Archive on MongoDB Atlas Today, we are announcing more innovations that unleash the full potential of business data, beginning with the general availability (GA) of Online Archive for MongoDB Atlas. With Online Archive, you can seamlessly tier your data across fully managed databases and cloud object storage, all while retaining the ability to query it through a single endpoint. Users can create a rule to automatically archive infrequently accessed data in their MongoDB Atlas clusters onto their object store, eliminating operational complexity and transactional data storage costs. All users on dedicated clusters (M10+) can use Online Archive regardless of which cloud provider they are using to run Atlas. If you want to learn more or see if Online Archive could help your organization, watch our deep-dive technical session , which is available on demand and features a live Q&A on Wednesday, Dec. 2 from 3:30-4pm ET. Online Archive gives me the flexibility to store all of my data without inucrring high costs, and feel safe that I won't lose it all. It's the perfect solution. Ran Landau, CTO, Splitit The power of choice Empowered developer teams around the world turn to MongoDB Atlas on their preferred cloud to deliver mission-critical services to their businesses faster. Here are a few customer success stories that are near and dear to our hearts: Ludo King : The small but mighty team of developers behind India’s favorite mobile game, Ludo King, turned to MongoDB Atlas and MongoDB Realm on AWS. The results? They’ve been able to keep building new, revenue-generating features for the game’s half a billion players, while efficiently managing near instantaneous 1000% growth. Toyota Materials Handling Europe : While building the connected warehouses of the future, Toyota Material Handling needed a database as flexible and powerful as MongoDB Atlas, running on Azure, to break down their monolith and transition to a microservices architecture. Boxed : Grocery delivery wholesaler Boxed built its platform on MongoDB Atlas on Google Cloud to accommodate the soaring demand for goods and services due to the pandemic. As brick-and-mortar retailers struggled to keep up with demand, Boxed saw a 30x spike in demand, which they were able to handle because of MongoDB’s powerful data platform. Get started with MongoDB Atlas today. And make sure you take advantage of all the opportunities to explore MongoDB at AWS re:Invent 2020 .

November 30, 2020
News

MongoDB Atlas Arrives in Italy | MongoDB Atlas Arriva in Italia

We’re delighted to announce our first foray into Italy with the launch of MongoDB Atlas on the AWS Europe (Milan) region. MongoDB Atlas is now available in 20 AWS regions around the world, including 6 European regions. Milan is a Recommended Region , meaning it has three Availability Zones (AZ). When you deploy a cluster in Milan, Atlas automatically distributes replicas to the different AZs for higher availability — if there’s an outage in one zone, the Atlas cluster will automatically fail over to keep running in the other two. And you can also deploy multi-region clusters with the same automatic failover built-in. We’re excited that, like customers in France, Germany, the UK, and more, Italian organizations will now be able to keep data in-country, delivering low-latency performance and ensuring confidence in data locality. We’re confident our Italian customers in government, financial services, and utilities in particular will appreciate this capability as they build tools to improve citizens’ lives and better serve their local users. Explore Atlas on AWS Today &nbsp; In Italian, courtesy of Dominic: Siamo lieti di annunciare la nostra espansione in Italia rendendo disponibile MongoDB Atlas nella regione AWS Europa (Milano). MongoDB Atlas è ora disponibile in 20 regioni AWS nel mondo, comprese 6 regioni europee. Milano è una Recommended Region ; questo significa che ha tre Availability Zones (AZ). Quando viene creato un cluster a Milano, Atlas distribuisce automaticamente le repliche sulle diverse AZ per aumentare la disponibilità e l’affidabilità — nel caso in cui avvenga un disservizio in una zona, il cluster Atlas utilizzerà la funzionalità di failover per restare in esecuzione sulle altre due. Eventualmente è anche possibile creare cluster multi-region che incorporano la stessa logica di failover automatico. Siamo felici che anche le realtà italiane possano scegliere, come i nostri clienti in Francia, Germania, UK, ed altrove, di mantenere i propri dati all’interno dei confini nazionali, dando risposte a bassa latenza ai propri utenti ed assicurando loro la fiducia nella localizzazione fisica dei dati. Siamo sicuri che i nostri clienti in Italia, in particolare nel settore pubblico, nei servizi finanziari, e nelle utilities, apprezzeranno queste nuove possibilità per la creazione di nuovi strumenti per migliorare la vita dei cittadini e servire meglio i loro utenti in Italia. Scopri subito Atlas disponiblie su AWS

November 4, 2020
News

Ready to get Started with MongoDB Atlas?

Start Free