10gen will be at OSCON, the Open Source Convention, this week to meet with other open source enthusiasts. Stop by Booth 706 to meet 10gen Engineers and pick up your MongoDB T-Shirt.
Catch talks from 10gen and the MongoDB Community at OSCON this week:
- MongoDB - From Zero to Sharded with Shaun Verch, MongoDB Kernel Engineer, 10gen on Monday, July 22 at 1:30PM in Portland 252.
- Choosing A Shard Key In MongoDB with Shaun Verch, MongoDB Kernel Engineer, 10gen Wednesday, July 24 at 1:40PM in E143.
- Creating a User Journey for Your Open Source Community with Francesca Krihely, MongoDB Community Marketing Manager, 10gen, Thursday July 25 at 2:30PM in E144.
- MongoDB on Amazon Web Services: Operational Best Practices with Charity Majors, Engineer at Parse at 10AM Friday in E145.
Deadline 6: Powered by MongoDB
Thinkbox Software recently announced Deadline 6 , the newest version of their render software, which is powered by MongoDB. Deadline is a render management tool, used heavily in the visual effects, broadcast and architectural industries. Thinkbox’s Deadline team chose MongoDB as their database of choice for its JSON-based document structure and speed at handling connections. A bit of background on render management for those unfamiliar: when making a film, production teams create and render thousands to millions of individual frames for the layers of their shots. Computers process your image data for compositing blue screens, characters or rendering fire, smoke and other special effects. “There are a lot of products that make this happen,” says Chris Bond, founder and CEO of Thinkbox Software. “They all render, control and work differently depending on your OS platform.” In the past, filmmakers or graphic specialists would manually split these jobs up between a number of machines to distribute the amount of data for processing jobs. There are thousands of frames in a shot, and thousands of shots in a movie. Some rendering processes could take 24 hours, while others could take 20 minutes. There wasn't the virtualization platform that could distribute these tasks and manage these processes, so they were typically done manually or executed by scripts. Deadline solves this problem as a management queue for rendering farms. Deadline 6's Monitoring Dashboard Deadline currently supports over 40 applications and operating systems across the board, and breaks up shots and frames into tasks across different machines. Many of this year’s summer movies such as Man of Steel, Iron Man 3, Oblivion, and 300: Rise of an Empire, are made with Deadline 6 and used MongoDB as the backend. The team switched to MongoDB in order to improve create a tool that could run fast while operating on tens of thousands of tasks at a time. Up until Deadline 5, the team was using an XML, file-based storage system which was easy for rapid development, like JSON, and it was schema-less, so they didn't have to worry about tables. “Deadline was designed as a ‘serverless’ architecture.” said Ryan Russell, lead developer on Deadline 6. “Rather than having a central application telling its clients what to do, the clients would go to a central data store, based on the data in there, it would take the next step.” The client would go to the storage location where these "jobs" are housed and would pick up and frame and then pick up another frame. “It was a solid backend for our software, because Deadline could never ’go down’ unless our server hosting that data went down.” But a file-based system is hard to scale and the team needed a way to help Deadline scale and hit higher performance numbers. When searching for a new solution, one of the developers stumbled across CouchDB. “It matched our document-based system, and when we investigated further, the team kept seeing MongoDB come up in searches and blog posts.” For them, the 1 to 1 XML to JSON mapping was a winning feature for both document stores, but to get a better understanding, they decided to build a prototype with each data store to see which one performed better. MongoDB won out in the end. “MongoDB handled hundreds of connections at the same time without any issue. CouchDB had a hard time because of the RESTful API overhead. The improved performance with MongoDB created such a great experience for the end-user. That was a huge thing for us.” Select clients recently went through a 6 month a beta program with Deadline 6, and after using it in production, were amazed at how much faster their system was with MongoDB as the backend. In Deadline, MongoDB functions as a task queue, and controls the management of third party render processes. Each day, a large film set might render over 25-30 Terabytes of data. MongoDB handles the process management of each job and controls the data movement. To the team MongoDB “seems like something we can stand on and scale in many orders of magnitude more than we have before.” Look out for a film powered by Deadline and MongoDB this summer.
Built With MongoDB: FanPlay
Pritesh Kumar and Bharat Gupta co-founded FanPlay Technologies at the beginning of the pandemic that shook the world in 2020. With their real money gaming (RMG) product, they’ve joyfully brought thousands of people together across India in a safe way, while establishing the country’s leading gaming app. For this segment of #BuiltWithMongoDB, we spoke with Pritesh about their company’s business model, how MongoDB is working to their advantage, and what celebrities are already utilizing their platform. MongoDB: What prompted you to build FanPlay? Pritesh: The emergence of COVID-19 really prompted me into the startup world again. I’ve been a founder in the past, and I knew that at this time a lot of new companies would emerge, so I decided to be part of that. The idea for FanPlay came from observing Cameo . I was really impressed by its strong viral growth and its monetization of influencers. I think these micro influencers on the platform, although they don’t make a lot of money for a single video, can add massive value to any business. And at the same time, we were looking at the RMG industry, which was and still is the fastest-growing space in online gaming. But there is a real problem of very high customer acquisition cost. So, we put one and one together and started building an influencer-led, RMG platform. We get influencers to host real-money trivia games for the fans and followers on our platform. Typically these influencers promote their own shows on their social media platforms. They gather an audience from YouTube, TikTok, and various other channels, and then they come to our platform for the gaming experience. The audience usually pays a small entry fee. From that entry fee, a prize is created, that prize goes to the winner of the game, and from that prize we take a cut. So this is our business model. MongoDB: What was your initial vision for the product, and what does it look like today? Pritesh: The product has changed a lot from what we initially envisioned. We started with a web app initially because we thought that acquiring users on the web would be much easier, but then we launched our free Android app and it did very well. From there we launched our paid-entry model. So the product has gone through three iterations so far. In the beginning we worked a lot with Instagram influencers and realized that we needed to be working with influencers on YouTube, and specifically with people more regionally significant to India, where most of our business is at the moment. We have also expanded to hosting established faces from Instagram and YouTube. MongoDB: Can you tell us about the scale of the platform? Pritesh: Currently we work with about 500 influencers that have a lot of visibility, and we host roughly 20,000 active users daily, from India. Typically we run about 20 games per day, and we’re working to scale that to 100 per day. MongoDB: What does your tech stack consist of? Pritesh: The app is built in React Native, and the back end is Node.js. Then of course for a database we use MongoDB. MongoDB was a very clear choice for us. From a professional standpoint, as an early-stage startup, you don’t know what your product will eventually turn into, right? How will it evolve in the next six months or a year? So it’s difficult to stick to a schema. Therefore, you need a lot of flexibility. Because of our need for flexibility, SQL was out of the question, so we needed to go with NoSQL. Once we decided on NoSQL, MongoDB became the obvious choice because of the community support and documentation. As a founder, I believe in really fast execution and putting your product out there, rather than waiting for a pitch-perfect product. And that demands a lot of flexibility from the business, product, and tech sides, because we need to be able to make immediate changes based on the features that are demanded and that catch the users’ attention. With MongoDB, we are able to try a lot of product variations or tweaks very quickly. MongoDB: As you've scaled, is there a particular MongoDB feature you've benefited the most from? Pritesh: There are a few features of MongoDB Atlas that have benefitted us a lot. One is the performance metrics. It’s really really amazing, actually. You can get a very clear picture of the state of your database in a single snapshot. It helps you buy time to focus on shipping your core product and the technology behind it. It removes your focus on database management and cluster management and just does it for you right out of the box. Also, Atlas handles all of the sharding and scaling. And something that I didn’t foresee but found very useful is its scalability. Startups tend to start at a scale where the free version of any cloud product would be good enough, right? But then you quickly move into a very different kind of need and scale. It just keeps on changing! Atlas gives us that flexibility to scale up really quickly with a very minimal amount of effort. MongoDB: Have you used any of the MongoDB for Startups services? Pritesh: Yes! We had a session with a technical advisor. I found it really helpful for addressing the key features we are launching in the future, and the main challenges we are going to face when building them. I was able to discuss those and was very satisfied. The session was really good for us. MongoDB: Who is the most well-known celebrity to have hosted a game so far on FanPlay? Pritesh: The comedian Kumar Varun ! MongoDB: Who is your favorite TV or game show host? Pritesh: Amitabh Bachchan , who is a household name in India for his acting and for his role as host of Kaun Banega Crorepati (India’s Who Wants To Be A Millionaire). MongoDB: What is your favorite podcast or blog? Pritesh: The InfoQ Podcast . It goes deep into how organizations build challenging tech products. Looking to build something cool? Get started with the MongoDB for Startups program.