MongoDB Blog
Announcements, updates, news, and more
LoanOptions.ai Scales AI-driven Finance Broking With MongoDB Atlas
Finance brokerage processes are known for being clunky and complex. It’s traditionally been very paper-heavy and manually intensive, with opaque and confusing credit policies, and it often takes weeks for borrowers to get an answer on whether their loan is approved.
Introducing MongoDB Agent Skills and Plugins for Coding Agents
Software engineering is evolving into agentic engineering. According to the Stack Overflow Developer Survey 2025, 84% of respondents use or plan to use AI tools in their development, up from 76% the previous year. At this rate, the tooling needs to keep pace.
Zomato Cuts $11M in Support Costs With MongoDB-Powered AI Platform
With more than 25 million active monthly users—and hundreds of millions of food delivery orders annually—Indian-born Zomato is the world's second-largest food delivery company. At the heart of the business’s success is Zomato’s ability to seamlessly scale, manage complex data, and build innovative AI-powered applications at pace.
The Modern End-to-End Digital Lending Journey Powered by MongoDB and Agentic AI
Traditional lending systems rely on disconnected legacy applications that were never designed for real-time data, automation, or digital-first customer experiences. Today, customers expect instant decisions, seamless digital experiences, and immediate transparency, while lenders must manage rising risk, regulatory pressure, and data complexity. Modern digital lending platforms are transforming this reality by unifying origination, decisioning, funding, and servicing into a single, intelligent workflow. In this article, we break down the end-to-end digital lending lifecycle and show how data-driven architectures are redefining how loans are created, approved, funded, and managed instantaneously.
Observability and OpenTelemetry: Introducing MongoDB Atlas Log Integration
In high-stakes enterprise environments, outages do not wait for business hours, and neither do IT/Network Operators. A latency spike hits the dashboard, and metrics signal that the database is under pressure. The cause? Indeterminate. Meanwhile, the business impact is immediate: orders fail to process, customers can’t access accounts, transactions stall, and critical records become temporarily unavailable. Every minute of uncertainty translates into lost revenue, frustrated users, and escalating pressure. Teams often fall back on a familiar—yet time-consuming—ritual: logging into their data platform, exporting large log files, extracting compressed archives, and manually searching through thousands of lines of entries to identify the issue. What should be a quick diagnosis becomes a manual context-switching investigation. By the time the problematic query, configuration issue, or audit event is identified, users have already experienced the disruption—and the business has absorbed the cost. MongoDB believes the database should be the heartbeat of a digital business. So we’re introducing a new log integration that brings MongoDB Atlas system and audit logs directly into external observability and storage platforms. This enhancement helps bridge the gap between metrics and meaning when it matters most. Flexible log delivery for modern observability workflows Now database operators, DevOps pros, and IT Operations teams alike can send MongoDB system and audit logs—including mongod, mongos, and audit logs—directly to the tools they already rely on: Datadog, Splunk, Google Cloud Storage, Azure Blob Storage, or Amazon S3. Beyond native integrations, MongoDB supports sending logs via OpenTelemetry (OTel), the open-source standard for collecting and transmitting telemetry data. This enables customers to export MongoDB logs to any observability or logging backend that supports OTel. By using a vendor-neutral, standards-based protocol, MongoDB fits seamlessly into modern observability architectures. This eliminates lock-in and preserves flexibility as tooling strategies evolve. Enabling real-time clarity Modern enterprises generate rich system logs essential for debugging and compliance. However, when these logs are siloed, operational inefficiencies grow. Manual log access introduces friction, delays resolution, and creates a visibility gap between metrics and logs. MongoDB’s new log integration transforms that experience with: Accelerated troubleshooting: Send logs in near real-time to observability platforms like Datadog, Splunk, or OpenTelemetry-compatible backends, enabling teams to quickly identify issues and reduce manual operational steps that slow incident resolution. Unified telemetry: Correlate MongoDB logs with application traces and infrastructure metrics in existing observability platforms, helping teams quickly understand how database behavior impacts overall system performance. Simplified compliance: Automatically route audit logs to secure long-term storage such as Amazon S3, helping organizations meet regulatory and audit requirements without manual log management. Figure 1. Atlas Log Integration configuration options for delivering MongoDB logs to observability and storage platforms. image Real-world use cases How does this look in practice for modern application, operations, and engineering teams? Here are a few examples. table The criticality of observability As applications scale, the database becomes the most critical layer of an organization’s technology stack. Missing or siloed visibility leads to costly downtime and fragmented decision-making. This log integration is available for dedicated M10+ clusters. An external sink can be configured in minutes: Navigate to the Project Integrations page in the MongoDB Atlas UI. Select the intended destination: Datadog, Splunk, Google Cloud, Microsoft Azure, Amazon S3, or any OTel log endpoint. Enter the required credentials and select the desired logs to send: mongod, mongos, or audit. Note: Atlas Search logs are also currently available via private preview. Figure 2. MongoDB Atlas logs integrated into an OpenTelemetry observability pipeline. image One observability strategy, built to scale For teams that need fast, MongoDB-centric visibility, MongoDB Atlas continues to offer powerful native tools like Query Insights and the Query Profiler. These capabilities are designed to surface what is happening inside a user’s clusters with minimal friction. However, as organizations scale, database insights can not live in isolation. MongoDB Atlas’s log integration extends observability systematically to the data plane. This enables MongoDB logs to flow into the observability platforms teams already use across engineering, security, IT operations, and compliance. With native integrations and an OpenTelemetry-compatible endpoint, teams can route logs wherever they are needed. This enables rapid troubleshooting, stronger auditability, and confident scaling without blind spots.
Atlas Stream Processing Now Supports Apache Avro With Schema Registry
MongoDB Atlas Stream Processing now supports Apache Avro serialization when integrated with the Confluent Schema Registry, removing key barriers that have made migrating streaming workloads difficult. You no longer have to choose between the flexibility of MongoDB and the performance of binary serialization. Whether you’re building real-time fraud detection, monitoring IoT sensor grids, or synchronizing microservices, MongoDB Atlas Stream Processing provides the tools to do it with confidence and at scale.
Asset Tokenization in Financial Services: MongoDB as the Data Foundation
For nearly more than a decade, tokenization has been one of the most talked-about concepts in financial services. From early blockchain pilots, to experimenting with real-world asset trading, to the DeFi boom (Decentralized Finance), the idea has been the same: transform traditional assets such as stocks, bonds, deposits, treasuries, or real estate into digital tokens that can move instantly and trade globally.
Scaling with Confidence: Introducing Standardized Atlas Admin API Rate Limiting
Managing a fleet of database clusters at scale requires precision, automation, and—most importantly—predictability. Today, MongoDB is excited to announce that standardized rate limiting for the Atlas Admin API v2 is now generally available (GA).
MongoDB and DigitalOcean: Empowering both Developers and Enterprises
Today, MongoDB is thrilled to announce the expansion of our strategic partnership with DigitalOcean. Together, MongoDB and DigitalOcean are doubling down on our shared mission: to empower developers and digital-native enterprises alike with the simple operations and scalable, and now AI-forward, innovative tools they need to build world-class applications.
Inside MongoDB Dublin: The Heart of Our International Growth
Nestled between the Irish Sea and the Wicklow Mountains, MongoDB’s Dublin office brings together people from around the world. It’s a place where you can build a meaningful career, contribute to leading global products, and feel part of a close-knit community. Located in Ballsbridge just south of Dublin city center, the office is a short walk from the Lansdowne DART station and is well-served by multiple bus routes, making it easy to plug into everything the city has to offer.