Introducing Pay as You Go MongoDB Atlas on AWS Marketplace

Eric Holzhauer
December 15, 2021 | Updated: September 27, 2022
#Atlas

We’re excited to introduce a new way of paying for MongoDB Atlas. AWS customers can now pay Atlas charges via our new AWS Marketplace listing. Through this listing, individual developers can enjoy a simplified payment experience via their AWS accounts, while enterprises now have another way to procure MongoDB in addition to privately negotiated offers, already supported via AWS Marketplace.

Previously, customers who wanted to pay via AWS Marketplace had to commit to a certain level of usage upfront. Pay as you go is available directly in Atlas via credit card, PayPal, and invoice — but not in AWS Marketplace, until today.

With this new listing and integration, you can pay via AWS with no upfront commitments. Simply subscribe via AWS Marketplace and start using Atlas. You can get started for free with Atlas’s free-forever tier, then scale as needed. You’ll be charged in AWS only for the resources you use in Atlas, with no payment minimum. Deploy, scale, and tear down resources in Atlas as needed; you’ll pay just for the hours that you’re using them.

Atlas comes with a Basic Support Plan via in-app chat. If you want to upgrade to another Atlas support plan, you can do so in Atlas. Usage and support costs will be billed together to your AWS account daily. If you’re connecting Atlas to applications running in AWS, or integrating with other AWS services, you’ll be able to see all your costs in one place in your AWS account.

To get started with Atlas via AWS Marketplace, visit our Marketplace listing and subscribe using your account. You’ll then be prompted to either sign in to your existing Atlas account or sign up for a new Atlas account.

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10 Signs Your Data Architecture is Limiting Your Innovation: Part 2

With the massive amounts of data organizations now ingest, store, and analyze comes a massive responsibility to monitor, manage, and protect it. Unfortunately, many businesses are functioning with little insight into how their data is stored and who is accessing it — and their overly complex data architecture can turn those challenges into Frail security can lead to unnecessary risk, and if you are not in control of your data architecture, the next big compliance offender or data breach victim could be you. These risks — and the time and resources required to address them — make up part of a hidden tax on your innovation. We call it DIRT — the Data & Innovation Recurring Tax . Our experts have identified 10 symptoms that can indicate your business is paying DIRT — read about them all in our white paper 10 Signs Your Data Infrastructure is Holding You Back , and check out Part 1 of this blog series. Here, we highlight two signs of this innovation tax that are all about security. Symptom #3: That last big data breach — or the next one — is on you The more complex your data architecture, the more threat vectors you need to cover and the more complicated and time-consuming it becomes to maintain security. Each data store and application may have its own security framework and requirements — its own access controls, role definition, and login procedures. Each database may in turn be connected with multiple other technologies and vendors, further adding to the time and complexity needed to keep everything secure. That’s a drag on your team: Some 30% of IT managers spend more than 16 hours a month just on patching, and 14% spend more than 48 hours a month. Often, it’s impossible to keep up: 42% of breaches are the result of an attack for which a patch was available but not applied, according to a Ponemon Institute study of IT professionals. On average, 28% of vulnerabilities remain unaddressed. Our Solution: With MongoDB's data platform, you have one set of database and data service components that share the same developer experience and the same underlying operational and security characteristics, making it a lot easier to defend. Organizations can use a single overarching security policy and implementation without having to reinvent the wheel every time someone has a new use case for the data. Maintaining audit logs and access is dramatically streamlined. You get both security and speed. Symptom #4: Rampant data duplication makes compliance a nightmare In a modern organization, every part of the business should have access to the data and insights that help optimize performance and meet customer demand. But most data is trapped in silos, each with its own formats, access, and authorization controls. Attempts to address data silo issues often create their own web of separate niche data technologies, each trying to solve the problem. That can create a lot of data duplication — so even your IT leaders may not know who has copies of which data, or even how many copies there may be. That’s obviously a problem for security reasons. It also makes it extremely difficult to comply with regulations such as GDPR and the California Consumer Privacy Act, or to respond effectively to audits. How can you tell your regulators exactly where personally identifying information sits, or where it has been, when you don’t even know how many copies exist? Our Solution: Eliminate silos in the first place by using MongoDB's data platform, which addresses many of the use cases that would otherwise spur teams to duplicate data. And, with MongoDB, you can federate queries across multiple sources so you don’t have to move data into different formats. Our next installment will focus on your developers’ time, how it’s spent and the price you pay when they can’t find the time to develop and roll out best-in-class features. For a complete view of DIRT, read our white paper DIRT and the High Cost of Complexity .

December 15, 2021
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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