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April 7, 2021

News

MongoDB Connector for Apache Kafka 1.5 Available Now

Soi cầu xổ số miền bắc Today, MongoDB has released version 1.5 of the MongoDB Connector for Apache Kafka! This article highlights some of the key features of this new release in addition to continuing to improve the overall quality & stability of the Connector . DeleteOne write model strategy When messages arrive on Kafka topics, the MongoDB Sink Connector reads them and by default will upsert them into the MongoDB cluster specified in the sink configuration. However, what if you didn’t want to always upsert them? This is where write strategies come in and provide you with the flexibility to define what you want to do with the document. While the concept of write strategies is not new to the connector, in this release there is a new write strategy available called DeleteOneBusinessKeyStrategy . This is useful for when a topic contains records identifying data that should be removed from a collection in the MongoDB sink. Consider the following: You run an online store selling fashionable face masks. As part of your architecture, the website sends orders to a Kafka topic, “web-orders” which upon message arrival kicks off a series of actions such as sending an email confirmation, and inserting the order details into an “Orders” collection in a MongoDB cluster. A sample Orders document: { _id: ObjectId("6053684f2fe69a6ad3fed028"), 'customer-id': 123, 'order-id': 100, order: { lineitem: 1, SKU: 'FACE1', quantity: 1 } } This process works great, however, when a customer cancels an order, we need to have another business process to update our inventory, send the cancellation, email and remove the order from our MongoDB sink. In this scenario a cancellation message is sent to another Kafka topic, “canceled-orders”. For messages in this topic, we don’t just want to upsert this into a collection, we want to read the message from the topic and use a field within the document to identify the documents to delete in the sink. For this example, let’s use the order-id key field and define a sink connector using the DeleteOneBusinessKeyStrategy as follows: "connector.class": "com.mongodb.kafka.connect.MongoSinkConnector", "topics":"FaceMaskWeb.OrderCancel", "connection.uri":"mongodb://mdb1", "database":"FaceMaskWeb", "collection":"Orders", "writemodel.strategy": "com.mongodb.kafka.connect.sink.writemodel.strategy.DeleteOneBusinessKeyStrategy", "document.id.strategy": "com.mongodb.kafka.connect.sink.processor.id.strategy.PartialValueStrategy", "document.id.strategy.partial.value.projection.type": "AllowList", "document.id.strategy.partial.value.projection.list": "order-id", "value.converter":"org.apache.kafka.connect.json.JsonConverter", "value.converter.schemas.enable":false, "document.id.strategy.overwrite.existing": true Now when messages arrive in the “FakeMaskWeb.OrderCancel” topic, the “order-id” field is used to delete documents in the Orders collection. For example, using the sample document above, if we put this value into the OrderCancel topic { “order-id”: 100 } It would cause the document in the Orders collection with order-id and value 100 to be deleted. For a complete list of write model strategies check out the MongoDB Kafka Connector Sink documentation . Qlik Replicate Qlik Replicate is recognized as an industry leader in data replication and ingestion. With this new release of the Connector, you can now replicate and stream heterogeneous data from data sources like Oracle, MySQL, PostGres and others to MongoDB via Kafka and the Qlik Replicate CDC handler . To configure the MongoDB Connector for Apache Kafka to consume Qlik Replicate CDC events, use “com.mongodb.kafka.connect.sink.cdc.qlik.rdbms.RdbmsHandler” as the value for the change data capture handler configuration parameter. The handler supports, insert, refresh, read, update and delete events. Errant Record Reporting Kafka Connect, the service which manages connectors that integrate with a Kafka deployment, has the ability to write records to a dead letter queue (DLQ) topic if those records could not be serialized or deserialized. Starting with Apache Kafka version 2.6, there was added support for error reporting within the sink connectors. This gives sink connectors the ability to send individual records to the DLQ if the connector deems the records to be invalid or problematic. For example, if you are projecting fields in the sink that do not exist in the kafka message or if your sink is expecting a JSON document and the message arrives in a different format. In these cases an error is written to the DLQ versus failing the connector. Various Improvements As with every release of the connector, we are constantly improving the quality and functionality. This release is no different. You’ll also see pipeline errors now showing up in the connect logs, and the sink connector can now be configured to write to the dead letter queue! Next Steps Download the latest MongoDB Connector for Apache Kafka 1.5 from the Confluent Hub ! Read the MongoDB Connector for Apache Kafka documentation . Questions/Need help with the connector? Ask the Community . Have a feature request? Provide Feedback or a file a JIRA .

April 7, 2021
Developer

Built with MongoDB: Gryphon Online Safety

Soi cầu xổ số miền bắc As friends and coworkers at an IoT company, John Wu and Arup Bhattacharya used to commiserate about the perils the internet posed for their children. It’s a problem most parents can relate to—especially now, when some children spend more than seven hours a day online. One day, John’s daughter saw something online that horrified him, and he and Arup decided they wanted to help bring the internet back into the hands of parents so they could curate online content for their children. With that, Gryphon Online Safety was formed. Gryphon is a cloud-managed network protection platform for homes and small businesses that blocks viruses, malware, and hackers while giving parents the chance to filter content and monitor what their children are doing. With $5.4 million in seed funding, more than 30,000 customers, and a team of 30 employees across three countries, Gryphon is growing quickly. The COVID-19 pandemic further accelerated adoption of Gryphon’s products; with children spending more time on devices at home and hacking activity increasing online, the company has seen a significant boost in users. In this edition of #BuiltWithMongoDB, we talk to CTO and Co-Founder Arup Bhattacharya and Senior Cloud Solutions Architect Sandip Das about the future of internet security and their experience building Gryphon with MongoDB. MongoDB: How has your business changed during COVID-19, given that families have been spending more time at home and online? Arup Bhattacharya: Our business has thrived during COVID. Although we typically add a thousand customers every month, during the pandemic that number has skyrocketed. More people are working from home and more children are attending virtual classes, which has caused families to think more about security and parental controls. Although we typically see two main cycles with our business, one in August and the other around the holiday season, our product isn’t that cyclical. People upgrade their hardware at different times, and when they look for high-performance mesh WiFi routers and security, we are an obvious solution. What’s funny is that while parents deeply appreciate our solution and the security it provides, children often hate us. I stumbled across a Reddit post in which a child wondered how he could get past the access filters his father had set up via Gryphon. Someone responded: “There’s nothing you can do but grow up and buy your own router.” With that said, there’s so much bad content out there—from bullying to games that hurt children—that it’s crucial we allow an easy way for parents to control the experience their children have online. MongoDB: At what point did you implement MongoDB, and what decision framework and criteria led to that decision? Sandip Das: We compared the big databases in terms of what solutions were available. We wanted something freely available for rapid prototyping and that made integration easy. For the back end, we use JavaScript with Node.js runtime, which is easily compatible with MongoDB. In fact, it’s the default choice for database integration. MongoDB owns its library, and combined with how simple the integration was, this made MongoDB a good choice for us. Another big factor was the storage. With MongoDB Atlas, you can have any number of servers, and you can quickly scale up to whatever your demands are. We developed the service from the beginning, and we were managing it ourselves. However, as the load has increased and more customers came on board, we thought it was time to seek out a better and more scalable solution that’s also easy to manage. That’s how we found MongoDB Atlas. With MongoDb Atlas autoscaling, we were able to achieve the flexibility we always wanted, along with automated backup solutions. MongoDB: Arup, you've held several senior engineering positions before becoming Co-founder and CTO of Gryphon. What advice would you give to others looking to follow that path? AB: The CTO position is very critical because it is the bridge between technology and business. The first thing you should think about when starting a company is the pain point you are solving. We started by first asking ourselves how our product will help society. How will it help people improve their lives? The starting point of a company shouldn’t just be to make money overnight. What will keep you motivated through the difficulty of building a business is thinking deeply about how your product will make a positive impact on people’s lives. Second, there inevitably will be low times and high times. At several points in the founder’s journey, you will experience real doubt and wonder whether you can really achieve your goals. The best thing to do is to keep on pushing for the highest-quality product possible. If your product is the best on the market and you are solving a genuine problem, the customers will find and appreciate you. Looking to build something cool? Get started with the MongoDB for Startups program.

April 6, 2021
Applied

Dive Deeper into Chart Data with New Drill-Down Capability

With the latest release of MongoDB Charts, you’re now able to dive deeper into the data that’s aggregated in your visualizations. At a high level, we generally create charts, graphs and visualizations of our data to answer questions about our business or products. Oftentimes, we need to “double click” on those visualizations to get insight into each individual data point that makes up the line, bar, column, etc. How the drill-down functionality works: Step 1: Right click on the data point you are interested in drilling down into Step 2: Click "show data for this item" Step 3: View the data in tabular or document format Each view can be better for different circumstances. For data without too many fields or no nested arrays, it might be quicker and more easily viewed in a table. On the other hand, the JSON view allows you to explore the structure of documents and click into arrays. Scenarios where more detailed information can help: Data visualization use cases are relatively broad spanning, but oftentimes they fall into 3 main categories: monitoring data, finding insights, and embedding analytics into applications. I’ll be focusing on the first two of these three as there are many different ways you could potentially build drilling-down into data via embedded charts. (Read more about our click events and embedded analytics ). For data or performance monitoring purposes , we're not speaking so much about the performance of your actual database and its underlying infrastructure, but the performance of the application or system built on top of the database. Imagine I have an application or website that takes reviews, if I build a chart like the one below where I want to easily see when an interaction hits a threshold that I want to dive deeper into, I now have the ability to quickly see the document that created that data point. This chart shows app ratings given after a user session in an app. For this example, we want to dive into any rating that was below a 3 (out of 5). This scatter plot shows I have two such ratings that cross that threshold. With the drill-down capability, I can easily see all the details captured in that user session. For finding new insights, let’s imagine I’m tracking how many transactions happen on my ecommerce site over time. In the column chart below, you can see I have purchases by month for the last year and a half (note, there’s a gap because this example is for a seasonal business!). Just by glancing at the chart, I can quickly see purchases have increased over time, and my in-app purchases have increased my overall sales. However, I want to see more about the documents that were aggregated to create those columns, so I can quickly see details about the transaction amount and location without needing to create another chart or dashboard filter. In both examples, I was able to answer a deeper level question that the original chart couldn’t answer on it’s own. We hope this new feature helps you and your stakeholders get more out of MongoDB Charts, regardless if you’re new to it or have been visualizing your Atlas data with it for months, if not years! If you haven’t tried Charts yet, you can get started for free by signing up for a MongoDB Atlas and deploying a free tier cluster.

April 6, 2021
Developer

How Three College Friends Became MongoDB Coworkers

Siya Raj Purohit, Chaitanya Varanasi, and Sohail Shaikh first met while attending the University of Texas at Austin (UT Austin) as undergraduate students. Five years after graduating, they found themselves brought together again — this time by MongoDB. I recently sat down with Siya, Chai, and Sohail to talk about this friendship that has been sustained through divergent career paths and continues to grow alongside their roles at MongoDB. Jackie Denner: Tell us about your story leading up to MongoDB. How did the three of you meet and begin to grow your careers? Siya Raj Purohit: I studied electrical and computer engineering at UT Austin from 2010 to 2013. Although Chai, Sohail, and I weren’t in the same year, we became friends from hanging out and working through the rigorous engineering curriculum in the same study lounge. Outside of the engineering building, Austin’s tech scene was exploding; some of my favorite memories with Chai and Sohail are going to tech events together. We met Stephen Wolfram (from WolframAlpha), briefly hung out with Mark Cuban, and crashed many SXSW tech events. Since graduating from college, I’ve lived in four states and worked across startups and venture capital firms. At MongoDB, I help provide founders with the resources they need to push the tech industry forward. Chaitanya (Chai) Varanasi: I am an electrical and computer engineering major from UT Austin, class of 2015 (Hook ‘Em!). Electrical and computer engineering is a fairly small cohort of students who all share a building and sit in the same hall for introductory classes. It is always said that the hottest fires forge the strongest metal. In our situation, we all had to go through grueling labs and coding assignments that would keep us up all night and unite us toward a common goal of passing that class. What started as collaboration on class materials very quickly transitioned into late-night frozen yogurt hangouts, playing Catan, and discovering Austin together. Sohail and I used to travel across the country for various hackathons, which was how we started our careers in software engineering. One of my favorite memories is of Siya taking us to the meetup of a lifetime at the Capital Factory, a startup incubator in Austin; we even got a picture with Stephen Wolfram! After graduating, I joined a large financial institution in Dallas as a software engineer, and then I began my presales journey in the performance space. After realizing the potential of data and understanding the value companies gain from data insights, I joined MongoDB. Sohail Shaikh: My journey in tech began when I was 12 years old and built my first computer. Since then, I have always been fascinated with new technologies and learning more about them. I was a math major at UT Austin, class of 2015. I actually can’t remember the first time I met Siya or Chai, because it seems as if I have known them forever, and I felt an immediate bond with both of them from the start. I have vivid memories of our times at UT together: attending hackathons, collaborating on ideas, and spending a lot of time talking about the future and how we could bring change. In the five-and-a-half years since graduating, I have worked in Palo Alto and Dallas — at a startup, at AppDynamics, and now at MongoDB. I’m excited to be reunited with Chai and Siya; we are all very passionate about making a positive impact in this world, and we are all doing that today at MongoDB! JD: What is your role at MongoDB? SRP: I’m helping the next generation of developers to build great companies. There is so much great talent coming out of universities and startup accelerator programs, and MongoDB for Startups works with developers to ensure they have the right products and services to transform their ideas into innovative companies. More than 1,500 companies have #BuiltWithMongoDB so far — and we’re super excited to continue growing the ecosystem. CV: I am a Senior Solutions Architect. My day-to-day job consists of being a technical partner to our rock-star sales team and performing proof of concepts with our customers to continually grow our MongoDB presence. SS: I am a Solutions Architect at MongoDB for the South Central region. My day-to-day job is working with customers in the presales organization and showcasing why MongoDB is so amazing. JD: How did you maintain your friendship after college? SRP: After college, I lost touch with Chai and Sohail for a couple of years. I moved to Silicon Valley, and although we periodically caught up through mutual friends, we didn’t really reconnect until we all joined MongoDB. I joined a few weeks before Chai (mostly to be part of his welcoming crew) and was ecstatic when Sohail told us he was joining MongoDB too. Now, we have a private Slack channel (named after one of our favorite Bollywood films) where we talk about our jobs and lives and also share cute memes and gifs. CV: Sohail and I both lived in Dallas and worked on the same team at a previous company. We have done multiple trips together and spent way too many nights eating sushi and Whataburger! Siya and I lost touch for a little because of the distance, but we were able to make up for lost time after joining MongoDB. SS: I am horrible at maintaining relationships, but Chai and Siya keep me in check (it’s just the type of people they truly are). I would meet Chai once a year on a group trip, and one day I called him to learn more about his new role at AppDynamics; he didn’t hesitate to refer me in. Next thing I knew, I was working with him on his team. Two-and-a-half years later, Chai decided to move to MongoDB, and I couldn’t resist. After working with Chai, I am now convinced I talk to him more than his wife does. Siya and I reconnected during the pandemic through a socially distanced meetup at a park while I was visiting San Francisco. Now that we both work for MongoDB, our friendship has picked up right where we left off. JD: All three of you joined MongoDB during the COVID-19 pandemic. How was the remote onboarding experience? SRP: Honestly, I was sort of nervous about joining remotely. I had left a company where I had really strong relationships with my coworkers, and it was daunting to imagine building new connections while being entirely remote. During my interview process, I asked for advice on how to best onboard. I was recommended the book The First 90 Days , which provided a great framework and onboarding roadmap. The MongoDB onboarding week itself was awesome — I met many people across the company, joined a few employee affinity groups (MongoDB Women is my favorite!), and learned about the lives of my coworkers beyond work — I even virtually met some of their babies and pets! I’m really excited to spend time with coworkers in person once it’s safer to do so. CV: I had a phenomenal experience with onboarding. Everyone at MongoDB has been nothing short of helpful. This was the first time in my life that I got to meet an entire executive team in a small group setting within the first month of joining the company. Each MongoDB executive hosts a coffee chat once a quarter, which is a great way to get to know them more personally. That kind of exposure is unparalleled, and it truly showed me how a great culture was supported from both bottom up and top down. SS: Onboarding at MongoDB is the best I have ever seen! Training and role clarity have been phenomenal, even in a remote setting. The material is organized and easy to grasp, and I don’t feel as if I have been left to figure everything out on my own. The team is extremely helpful in answering all of my questions and helping me grow. In Sales, there is also boot camp, which is divided up into two parts for my role. Boot camp lasted for a month to avoid any Zoom fatigue (given that we are all virtual), which also gave us more time to work on our assignments and properly learn the lay of the land. JD: What are you most excited about? SRP: I am so excited about Chai moving to NYC so we can work out of the same office when it reopens. I’ve already mapped out the top 10 bubble tea shops in NYC for us to visit. CV: I am ready to explore New York with Siya and have future MongoDB lunches together. Sohail and I are ready to tackle our Sales Kickoff and have fun when we return to normal situations after the pandemic. We are all career-driven individuals, and I am excited to see how we can uplift each other as a family. SS: I am most excited to be learning about the database space and contributing to growing the business. I am also super excited to see where MongoDB goes in the future. As one of the world’s fastest-growing databases, it feels as if we are on a rocket ship. JD: What advice would you give to others who are looking for a new role? SRP: Recruiting is always hard. Find unique ways to showcase why you’re a fit for a certain role or company — passion is seen and rewarded. CV: Always keep your connections and networks alive. Keep interacting with the folks you care about. I am nothing without my work friends and my work family. MongoDB is on a rocket ship right now, and you will absolutely love working here. SS: Don’t be afraid to take a risk in your careers, and put in an application to MongoDB today! We love working with talented, hard-working folks, and the grass is truly green on this side! Interested in pursuing a career at MongoDB? We have several open roles on our teams across the globe and would love for you to build your career with us!

April 1, 2021
Culture

Built with MongoDB: ADEx

Anyone who has reviewed legal documents knows how tedious and time-consuming the process can be. In the high-stakes, detail-oriented legal environment, even experienced lawyers or paralegals can make mistakes. And those mistakes can be expensive. Enter ADEx . ADEx is an online legal document due-diligence platform that is transforming the way people interact with legal and financial documents. “Computers never get tired, no matter how many pages your legal document contains or how dense its language,” says ADEx Co-Founder and CTO Apoorv Khandelwal . “Our platform can abstract your legal documents faster and more reliably than a paralegal.” The company has hosted more than 7 million contracts and partnered with large companies including Salesforce, Box, and Colliers International. As part of our #BuiltWithMongoDB series, we spoke with Apoorv about the company’s growth, its tech stack, and his experience scaling with MongoDB. MongoDB: What's ADEx's tech stack like? Apoorv Khandelwal: For our back end, we use the Java-based Play and Spring frameworks. We use Angular for the front end and Electron for the desktop app. For various predictions, we have Python Flask applications, and the deep learning models themselves are trained with TensorFlow and Keras. Our cloud provider for servers and application deployment is Kubernetes. We use various AWS services for storing clients’ legal documents, machine learning models, and other files. But the majority of our application data — ranging from contract summaries to our provision library to user events — is stored in MongoDB. MongoDB: How did you decide to use MongoDB? AK: Having worked at Amazon as a software development engineer, I was familiar with SQL databases and Hadoop. The team focused on machine learning, so its input data formats and sources were constantly evolving. My experiences showed me the pain associated with keeping SQL schemas up to date. When the choice came for ADEx, it was clear to me that we couldn’t use SQL. My experiences in successful startups showed me how we could successfully leverage the flexibility and scalability of MongoDB. I had worked before with Dynamo and other NoSQL platforms, but we didn’t want to get tied down to specific cloud providers. There were conversations about graph databases such as Neo4j as well, but they were not ideal for the majority of our queries that execute bulk data scans or do not start from a known data point. In the end, MongoDB’s flexibility and large community support made it the best choice. Later, upon joining the Techstars Accelerator in 2019, we were able to get credits through the Techstars and MongoDB for a startups partnership. We worked with a technical advisor at MongoDB to set up private connections from our applications. The learning curve was very short compared to other databases I had used; the basic concepts were clear, and the documentation guided me through the more complex data modeling and architecture decisions. Between features such as end-to-end encryption, auto-scaling, and automated backups, much of the basic database management work is now handled by MongoDB Atlas. MongoDB: How has MongoDB been for you as you've scaled? AK: With Atlas, I don’t have to worry about scaling anymore. Given how intuitive and easy to use it is — especially with the metrics and visualizations — it has solved a bunch of problems. I don’t even have to think about storage, because the database capacity automatically adjusts based on current data usage. Often for SQL, a team of database engineers may be needed for managing and running the database. With Atlas, we don’t need any dedicated person at all. We’ve been pleasantly surprised by the gentle learning curve while gradually utilizing more MongoDB features. For example, as we’ve introduced more-sophisticated use cases in our products, and we have enjoyed using MongoDB’s powerful aggregation framework to offload data processing from our application servers. We have an M30 cluster for cloud, and M20 for QA. MongoDB: What advice do you have for developers hoping to someday become CTOs? AK: Three things. First, get prior experience at a successful startup with a small engineering team. You will witness firsthand the growing pains a CTO has to deal with. These practical lessons can be invaluable for your own venture. Second, act as a filter between the business and technical teams. Imagine filling a small plate with food from a giant buffet. In a startup, the technical team has a limited capacity with which to build features or maintain the product. You should actively filter the flow of incoming ideas and features. Prioritizing the most crucial ones will prevent overflowing the technical team’s capacity while ensuring maximum value for customers. And third, get good technical mentors. It’s difficult to design sufficiently abstract data models that anticipate all potential future pivots. But a good debate with mentors can save plenty of technical debt later on. The first years were hard for me until I got technical mentors, such as Lalit Kapoor and Mihai Strusievici through Techstars. Looking to build something cool? Get started with the MongoDB for Startups program.

March 30, 2021
Applied

Announcing the MongoDB SI Architect Certification Program for Modernization to the Cloud

Soi cầu xổ số miền bắc You know the value of modernization as a strategic initiative. It’s not only about refreshing your portfolio of legacy applications with the latest innovations simply for the sake of moving to the cloud. This is much more than just “lift and shift”. True modernization is about realizing your company’s full potential and gaining a competitive edge through development methodologies, architectural patterns and technologies. And by modernizing with MongoDB, you can build new business functionality 3-5x faster, scale to millions of users wherever they are on the planet, and cut costs by 70% or more. If you’re familiar with our technology and our Modernization Program , you already understand the benefits. But do your customers? And, if not, how do you tell them? To help you get started, the MongoDB Partner team has created the MongoDB SI Architect Certification , a full scale kit of assets related to modernization. This free, self-paced certification helps you improve the modernization experience for a variety of customer types as well as drive conversations with customers around data center exit plans and application qualification for assessing cloud data platforms. Consider this certification the next step in deepening your expertise so you can expand your business opportunities and help customers modernize to the cloud. Customized for System Integrator partners, our certification teaches you how to discuss the benefits of modernization with various customers on a cloud journey. It enables architects to have deep discussions on vertical-based stories, migration tools, best practices, and architecture guidelines. System Integrator partners will also learn the fundamental value of offerings, messaging, objection handling, and more. Most importantly, this certification program equips SI architects with the ability to communicate key takeaways to the customer in a language they understand. Program Structure The free SI Architect certification program is self-paced, takes approximately 40 hours, and divided into six key sections, complete with a final certification exam. Introduction allows partners to access the modernization webinars and modernization program offerings. Top use cases focus on how MongoDB is used in business-wide strategic initiatives, like legacy modernization, cloud data strategy, microservices and more vertical based stories. Customer case studies highlight how MongoDB is deployed and leveraged through real-life customer case studies and proof points. University classes allow participants to leverage MongoDB university on-line as well as on-demand courses relevant to the architects. Competitive edge helps architects understand the true value of MongoDB in comparison to the competition. Final certification culminates the program with a "Talk to the experts" session and final certification exam where participants take a real world industry use case or customer project and assess how to migrate to the cloud. Our “Talk to the experts” session provides users with the opportunity to query experts with questions about the final certification exam. It also introduces the messaging around “MongoDB: The Intelligent Operational Data Platform” and details an Atlas TCO and sizing exercise. In addition to these assets, partners also have access to self-paced developer training and database administrator training here . Note: Download the enhanced Modernization Guide to refresh your knowledge on MongoDB modernization Dive Deeper into MongoDB Cloud Technology What’s one key lesson we know for certain? The data management platform you choose is a key factor in successfully migrating legacy applications to the cloud. The MongoDB Cloud section of our Architecture Guide discusses the unique value MongoDB can bring to organizations making the transition to cloud. Note: Download the Architecture Guide to refresh your knowledge on MongoDB Cloud The key components of the MongoDB cloud platform are: At its core is MongoDB , the general purpose operational database for modern applications. Nearly every application needs a fast database that can deliver single digit millisecond response times; and when it comes to speed, MongoDB delivers. With our flexible document data model, transactional guarantees, rich and expressive query language, and native support for both vertical and horizontal scaling, MongoDB can be used for practically any use case, reducing the need for specialized databases even as your requirements change. With multi-cloud clusters on MongoDB Atlas , customers can realize the benefits of a multi-cloud strategy with true data portability and a simplified management experience. Multi-cloud clusters provide the best-in-class technology across multiple clouds in parallel, migrate workloads across cloud providers seamlessly, and improve high availability with cross-cloud redundancy. Realm Mobile Database extends this data foundation to the edge. Realm is a lightweight database embedded on the client side. Realm helps solve the unique challenges of building for mobile, making it simple to store data on-device while also enabling data access when offline. Realm Sync is seamlessly integrated and keeps data up-to-date across devices and users by automatically syncing data between the client and a backend Atlas cluster. Ready to boose your knowledge and expertise? The Modernization Guide, Architecture Guide, and SI Architect certification program are waiting for you. Get started today. Start the free MongoDB SI Architect certification program today!

March 24, 2021
Home

MongoDB.Live Innovation Awards

Nominations are now open for the eighth annual MongoDB Innovation Awards. The Innovation Awards honor organizations and teams that are pioneering new ways to use data, expanding the limits of technology, and enhancing their businesses with MongoDB. We invite you to nominate any organization or individual that is building something dynamic, interesting, or unexpected with MongoDB. .live Innovation Awards Page All winners will receive a physical trophy for their display case, a digital ribbon for their website, an in-depth feature story on MongoDB.com, recognition during the .live event, detailed profiles on our event website, and inclusion in our Innovation Awards press release and blog post. View terms and conditions . Past recipients include 7-Eleven, Toyota Connected, dacadoo, Nationwide Building Society, Pizza Hut, Spathe Systems, Zinc and Charles Schwab. Read more about last year’s winners here . We invite you to nominate yourself, your company, a colleague, a partner, or anyone who is building something exciting with MongoDB. Submissions are open now through April 15, 2021. Award categories appear below. We look forward to your nominations! Award Categories: Certified Professional of the Year A Certified Professional who has used their skill set to positively impact the MongoDB community. Customer First An Organization that created a more meaningful, personalized, and improved customer experience. Data for Good An Innovator who took on some of the more challenging issues affecting society and the planet in order to transform the future and make the world a better place. From Batch to Real-Time An organization who built an event-driven architecture with MongoDB that makes streams of data from source systems available in real time. Going Global An Organization that geographically expanded their cloud data infrastructure with MongoDB Atlas, while remaining in compliance with regional data privacy measures and local regulations. Industry Transformation A Change-Maker who moved their business to the next level and disrupted their industry by identifying new technologies, applying new skills, or increasing operational efficiency. Front Line Heroes Our world has changed dramatically since Covid-19. This award is to recognize technologists who have embraced the power of technology to solve some of the unforeseen challenges of Covid-19. Jackpot An Organization that realized tremendous value from MongoDB and has seen it make an impact on its bottom line (time savings, cost savings, and/or reduction in operational complexity). Partner of the Year A MongoDB Partner who has integrated MongoDB into its offerings in order to deliver massive value to our joint customers. Savvy Startup This award is for one of the brightest rising stars to graduate from our MongoDB for our StartUps program. The William Zola Award for Community Excellence A person recognized by the MongoDB community for outstanding contributions in knowledge exchange, facilitating connections, and creating a welcoming experience for all members. Unbound An Organization that built a best-in-class mobil application, using MongoDB Realm.

March 22, 2021
Events

Built With MongoDB: Workast

Soi cầu xổ số miền bắc In 2016, Guillermo Gette was a technical lead at Expedia focusing on the front end development of its Australia and New Zealand websites. Like so many others, he was using Slack to communicate with team members. While Slack enabled rapid and collaborative communication, it didn’t do much to keep his team organized. So Guillermo kept a notepad close by to write to-do lists based on Slack messages, as well as a spreadsheet to manage developer tasks. But Guillermo soon realized that this practice made no sense. Why couldn’t he just put all these lists in Slack? Guillermo first built a simple bot that put a to-do list inside a Slack conversation and then published the app in the Slack Marketplace. Encouraged by growing demand from users interested in his tool, Guillermo founded Workast , a full-featured project management system embedded in Slack that is used actively by more than 50,000 people at companies large and small. Workast has raised $1.85 million from investors Greycroft Partners, Spider Capital, Mucker Capital, and Dream Incubator. In this #BuiltWithMongoDB story, Guillermo shares his vision for Workast and what he’s learned along the way. Before you started Workast, you were just trying to solve the problem for yourself. Let's talk about how you got started. In 2016, Slack was still an early-stage startup, and it was becoming quite popular in the tech community. I realized I could save a lot of time if I had a simple bot inside of Slack that captured to-do items from Slack conversations and created an environment inside of Slack to organize and communicate about projects. At the beginning, I was really putting my skills as a software developer to work to just build something for myself. The initial idea was to quickly capture a part of a conversation and turn it into a to-do item. Then you could seamlessly move from Slack into Workast and manage lots of different to-do lists to get work done. But once I saw how people used Workast, it became clear that for smaller organizations, the app became how the whole company ran. And for larger companies, Workast organized the work in (and eventually across) departments. People were drawn to the fact that they didn’t have to keep switching between communication and collaboration to project management. You didn’t have to invite people to join a project. They were there already because they were in Slack. What were some of the challenges you faced early on? When I put the app on the Slack marketplace, it took off right away and then two things happened. First, I got questions about new features. People wanted more ability to organize the tasks, tag them, and report on them in the Slack channel from which they originated. We started improving the product as fast as possible based on user feedback, and that led to more traction. The second thing that happened was we realized we were in a red ocean market, which means lots of players. People have used many of the mature project management and to-do apps out there and have high expectations. Our advantage in one sense was that we were embedded in Slack. In another sense, we were playing catch-up from the minute we went live. People loved the app, but then they’d also say, “Hey, I also need sub-tasks, assignments, projects, and deadlines.” They wanted templating, repeated tasks, tagging, advanced reporting, visualizations, commenting, and search, all the stuff they were used to. There is a lot of functionality that doesn’t sound exciting, and it doesn’t sound innovative, but people really wanted it in our product, and we had to build it quickly. Reducing the time from idea to implementation was crucial. There's a moment in every entrepreneur's journey when they realize that their product can become an actual company. When did it feel like you had a real business on your hands? At the beginning, it was mostly individuals and startups. Then, the Slack marketplace opened the door to a lot of other companies. Teams at Expedia, IBM, PayPal, and MongoDB started using Workast too. It was clear that we had hit a chord across a large market. The arrival of bigger companies was good news, of course, but also a challenge because we had to pass reviews by security, IT, and procurement, which means lots of work attending to certifications, documentation, and integrations. We then had to figure out how to build a business and capture the value we were creating. Pretty quickly, people started asking when we were going to start charging. They saw the value and expected they would have to pay for it at some point, which was a good sign. Our strategy was to focus on product-led growth. We decided not to focus on revenue but to allow people to use the product and eventually realize that upgrading made sense. So we don’t have a 30-day trial but rather we put counters on certain features: you can use them 10 times and then you are asked to upgrade. Why did you decide to build Workast on MongoDB? When you start a company, you don’t really know where your product — or your customers — are going to take you. You want the cost of change and evolution to be as low as possible. You want to move fast. That makes MongoDB, a schema-less database built for flexibility and experimentation, the right solution. The cool thing is that as our company and our product have evolved, our database has evolved with us. We’ve never had to suffer downtime to update schemas or write migration scripts. Time to market was crucial for us, and MongoDB accelerates that. MongoDB also scales and keeps on scaling. More than five million tasks have been created in Workast. Those tasks have to be actively there, they have to be searchable, and they have to be indexed. We don’t need to worry about it. We use MongoDB’s Performance Advisor every week, which tells us about performance problems and helps identify missing indexes, helping us make sure we’re scalable. Right now our cluster doesn’t need sharding, but when we do, it’s there for us. MongoDB is a database we can rely on — now and as we grow. What features of MongoDB have proven to be most helpful? Our architecture is based on Node.js and the AWS Lambda serverless platform. We use MongoDB’s in-database triggers to both automate actions in the database and also call out the Lambda functions. Our database is growing and now we have users that have years of data in Workast. We realized that at some point, we will probably want to move older data out of production into an archive. Again, MongoDB has a plan for moving data to object storage in a data lake but still allowing it to be searchable. When we need it, we will use it. We use MongoDB Atlas, so everything is hosted by MongoDB in the Cloud, run by MonogoDB, with lots of automation. Operations are really simple from our point of view. Our goal is to offload responsibility for everything that doesn't drive differentiating value. Uptime and scalability matter but we can push a lot of that responsibility to the Cloud. We think about MongoDB as much as we want to. Not more. MongoDB acts as our database administrator, making sure the servers are updated so we can focus on building our software and business. Looking to build something cool with MongoDB? Get started with the MongoDB for Startups program.

March 18, 2021
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