Javascript All Over with MongoDB and Node.js

Francesca Krihely
May 30, 2013 | Updated: May 22, 2015
#mongodb#Node.js

Developers have often called MongoDB and Node.js a “match made in heaven,”. Node.js’s powerful event-based concurrency framework matches well to MongoDB’s real-time capabilities, and has made it simple to run new projects with end-to-end JavaScript. Over the past few weeks, there’s been a lot of activity in the MongoDB and Node.js communities.

Industry Validation

  • The MongoDB and Node stack entered the enterprise: eBay’s engineering team announced their first Node.js project, called “Talk”, powered by MongoDB. This particular project had to be “as real-time as possible,” and handle heavy I/O operations, pushing eBay to switch from their typical Java workflow to Node.js.
  • 10gen, Joyent, Clock and Nodejitsu all gave an update on the state of the Nodestack on May 21.
  • Strongloop, a startup that employs some of Node.js’s core contributors, just launched their first enterprise distribution of Node.js. This is appealing to growing enterprise need for an out-of-the-box distribution with pre-installed modules and advanced features like private NPM repos.

Community Enthusiasm

On a period of 2 weeks, MongoDB User Groups in New York City, Atlanta, San Francisco, Silicon Valley and Boston hosted presentations on Node.js. The New York City MongoDB User Group hosted a talk on the “MEAN” stack (MongoDB, ExpressJS, AngularJS and Node.js), and Val Karpov started with an overview of why MongoDB and Node.js are winning in the developer community.

  • MongoDB’s flexible data model makes it simpler to write applications, leaving minimal mental translation from tables to objects. With dynamic schemas, there is no need to keep data consistent with schemas, as is the case with RDBMS. Thinking about objects instead of tables eases development for the long term.
  • Thousands of APIs are readily available and with Node.js you can perform a lot of I/O requests and start many connections at the same time without having a large memory overhead. It’s all done in one single-threaded event loop.
  • If you’re handling most of your data on the front end in JSON, writing a query in SQL isn’t so valuable. With MongoDB and Node.js, you can handle JSON on both the front-end and at the server level.

Javascript Everywhere

The Node.js and MongoDB stack is more than just hype: the stack is meeting requirements for real-time applications in the enterprise and drumming up global community adoption. PaaS providers such as MongoLab, Windows Azure and Nodejitsu among others are betting big on wide Node.js adoption, and gaining traction. We expect to see more JavaScript everywhere.

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Go Agent, Go

Discuss on Hacker News 10gen introduced MongoDB Backup Service in early May. Creating a backup service for MongoDB was a new challenge, and we used the opportunity to explore new technologies for our stack. The final implementation of the MongoDB Backup Service agent is written in Go , an open-source, natively executable language initiated and maintained by Google. Why did we Go with Go? The Backup Service started as a Java project, but as the project matured, the team wanted to move to a language that compiled natively on the machine. After considering a few options, the team decided that Go was the best fit for its C-like syntax, strong standard library, the resolution of concurrency problems via goroutines, and painless multi-platform distribution. mgo As an open-source company, 10gen is fortunate to work with MongoDB developers around the world who build open-source tools for new and emerging languages to provide users with a breadth of options to access MongoDB. One of the MongoDB Masters , Gustavo Niemeyer , has spent over two years building mgo , the MongoDB driver for Go. In that time he’s developed a great framework for accessing MongoDB through Go and Gustavo has been a valuable resource as we’ve built out the Backup Service. In his own words : “It’s great to see not only 10gen making good use of the Go language for first-class services, but contributing to that community of developers by providing its support for the development of the Go driver in multiple ways.” Programming the backup agent in Go and the mgo driver has been extremely satisfying. Between the lightweight syntax, the first-class concurrency and the well documented, idiomatic libraries such as mgo, Go is a great choice for writing anything from small scripts to large distributed applications. Starting a Java project often begins with a group debate: “Maven or Ant? JUnit or TestNG? Spring or Guice?” Go has a number of conventions through which Go team has created a sensible, uniform development experience with the holy trinity of tools: go build, test and fmt. The organization of source code and libraries is standardized to allow using the go build tool. See details here Name test files as XXX_test.go with functions named TestXXX can be run automatically with go test Braces are required on if statements and the first brace goes along with the if condition. E.g. if x { doSomething() } instead of: if x { doSomething() } Methods that end with an f (e.g. Printf, Fatalf) means a string formatted method will be validated in go vet that the number of substitutions (e.g. %v) matches the number of inputs to the function. mgo is a real pleasure to use with high-quality code, thorough documentation and an API that is a thoughtful, natural blend of idiomatic Go and MongoDB.  Our team owes a lot of thanks to Gustavo for his hard work on this project. There are other Go projects being explored at the moment and we hope to see more people using mgo in production going forward. By the 10gen Backup Team

May 29, 2013
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Hanabi Technologies Uses MongoDB to Power AI Assistant, Hana

For all the hype surrounding generative AI, cynics tend to view the few real-world implementations as little more than “fancy chatbots.” But for Abhinav Aggarwal, CEO of Hanabi Technologies, the idea of a generative AI-powered bot that is more than just an assistant was intriguing. “I’d been using ChatGPT since it launched,” said Aggarwal. “That got me thinking: How could we make a chatbot that was like a team member?” And with that concept, Hana was born. The problem with bots “Most generative AI chatbots do not act like people; they wait for a command and give a response,” said Aggarwal. “We wanted to create a human-like chatbot that would proactively help people based on what they wanted—automating reminders, for example, or fetching time zones from your calendar to correctly schedule meetings.” Hanabi’s flagship product, Hana, is an AI assistant designed to enhance team collaboration within Google Chat, working in concert with Google Workspace and its suite of products. “Our target customers are smaller companies of between 10 and 50 people. At this size you’re not going to build your own agent from scratch,” he said. Hana integrates with Google APIs to deliver a human-like assistant that chimes in with helpful interventions, such as automatically setting reminders and making sure meetings are booked in the right time zone for each participant. “Hana is designed to bring AI to smaller companies and help them collaborate in a space where they are already working—Google Workspace,” Aggarwal explained. The MongoDB Atlas solution For Hana to act like a member of the team, Hanabi needed to process massive amounts of data to support advanced features like retrieval-augmented generation (RAG) for better information retrieval across Google Docs and many other sources. And with a rapidly growing user base of over 600 organizations and 17,000+ installs, Hanabi also required a secure, scalable, and high-performing data storage solution. MongoDB Atlas provided a flexible document model, built-in vector database, and scalable cloud-based infrastructure, freeing Hanabi engineers to build new features for Hana rather than focusing on rote tasks like data extract, transform, and load processes or manual scaling and provisioning. Now, MongoDB Atlas handles a variety of responsibilities: Scalability and security: MongoDB Atlas’s auto-scaling and automatic backup features have enabled Hanabi to seamlessly grow its user base without the need for manual database management. RAG: MongoDB Atlas plays a critical role in Hana’s RAG functionality. The platform enables Hanabi to split Google Docs into small sections, create embeddings, and store these sections in Atlas’s vector database. Development Processes: According to Aggarwal, MongoDB’s flexibility in managing changing schemas has been essential to the company’s fast-paced development cycle. Data Visualization: Using MongoDB Atlas Charts has enabled Hanabi to create comprehensive dashboards for real-time data visualization. This has helped the team track usage, set reminders, and optimize performance without needing to build a manual dashboard. Impact and results With MongoDB Atlas, Hanabi can successfully scale Hana to meet the demands of its rapidly expanding user base. The integration is also enabling Hana to offer powerful features like automatic interactions with customers, advanced information retrieval from Google Docs, and manually added memory snippets, making it an essential tool for teams around the world. Next steps Hanabi plans to continue integrating more tools into Hana while expanding its reach to personal Gmail users. The company is also rolling out a new automatic-interaction feature, further enhancing Hana’s ability to proactively assist users without direct commands. MongoDB Atlas remains a key component of Hanabi’s stack, alongside Google Kubernetes Engine, NestJS, and LangChain, enabling Hanabi to focus on innovating to improve the customer experience. Tech Stack MongoDB Atlas Google Kubernetes Engine NestJS LangChain Are you building AI apps? Join the MongoDB AI Innovators Program today! Successful participants gain access to free MongoDB Atlas credits, technical enablement, and invaluable connections within the broader AI ecosystem. If your company is interested in being featured, we’d love to hear from you. Connect with us at ai_adopters@mongodb.com.

November 21, 2024