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10 Years of MongoDB Atlas: Built for What’s Next
June 25, 2026
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Atlas Stream Processing Brings Operational Data to Apache Iceberg
Every order placed, message sent, or sensor reading captured lands in an operational database. Analysts, data scientists, and AI teams all want that data, because the freshest signal about a business lives in the systems running it. But getting this data from the application layer to the lakehouse, continuously and at scale, has been one of the most stubborn problems in the modern data stack.
Improving Agent Retrieval with Native Reranking and Hybrid Search
In production AI, what the system retrieves shapes everything that follows. It determines whether an application surfaces the right context in the first place and how much irrelevant information gets passed to an LLM. That affects two things you care about most: answer quality and cost.
MongoDB Search and Vector Search Now Run Anywhere
MongoDB is excited to announce the general availability of MongoDB Search (full-text) and Vector Search for MongoDB Enterprise Advanced and MongoDB Community Edition. Since announcing the public preview at MongoDB.local New York last year, these milestones represent MongoDB’s commitment to ensuring developers can build intelligent, search-driven applications wherever their data lives without compromising on capability, data control, or infrastructure flexibility.
Retrieval Accuracy Is Now a Competitive Advantage
The token economy is here. And as soon as you have an economy, people start budgeting. So it’s no surprise that most conversations about AI now come back to the token budget. Teams are being asked to show the value of inference—the action phase of AI—spend and justify the cost. The answer traces back to the data that was retrieved and fed to the LLM. This step is intuitively referred to as “retrieval.”
Run AI Wherever Your Compliance Framework Demands
The CTOs I talk to in regulated industries aren’t debating whether to build with AI. That decision has been made. What they're navigating is a harder question: how do you build AI at the standard your compliance framework requires, when most of the tooling was designed for environments you're not allowed to use?
MongoDB to Upskill Two Million Builders in India by 2030
Organizations across India are racing to take AI applications from experimentation to full-scale production, but the bottleneck is almost never the AI model—it's the data layer. That's why data infrastructure skills are so important to the AI economy, and it's why we're so excited to share that today at MongoDB .local Bengaluru, we announced plans to upskill two million Indian builders by 2030 through new local language initiatives and regional partnerships. The expanded MongoDB for Academia program will help equip the next generation of builders with the cloud, data, and AI skills required to scale India’s digital economy.
10 Years of MongoDB Atlas: Built for What’s Next
Nearly a decade ago, I joined MongoDB as a Senior Product Manager to help build the company’s new cloud product, MongoDB Atlas. Our customers had been telling us they wanted to bring MongoDB’s familiar developer experience to the cloud, with the reliability and confidence teams needed to run in production. Atlas was our answer.
BAAC Transforms Rural Banking With MongoDB-Powered Mobile App
One of Thailand’s largest state-owned banks, the Bank for Agriculture and Agricultural Co-operatives (BAAC), serves over 32 million customers and 7 million farmer households across Thailand. BAAC is focused on rural development, and the bank provides essential funding, knowledge, technology, and value-added services to Thai farmers.
Celebrating Graduation Season with MongoDB Student Projects
Welcome to a showcase of student innovation from KL University Hyderabad! In this blog post, we spotlight outstanding projects developed by KL University Hyderabad students using MongoDB in their Python Full Stack Development curriculum. These projects exemplify the creativity, technical expertise, and social consciousness of the students. Under the mentorship of Professor Chanda Raj Kumar, the integration of MongoDB into the students’ Python Full Stack Development journey has not only expanded their technical skillset but also allowed them to address pressing real-world challenges.