MongoDB

What MongoDB does

MongoDB, Inc. (NASDAQ: MDB) is a publicly traded document-oriented NoSQL database company founded in 2007, headquartered in New York, with international headquarters in Dublin, Ireland. The company's core technology is a JSON-native document database with horizontal scalability and flexible schema, packaged as MongoDB Atlas (the fully managed multi-cloud developer data platform), MongoDB Enterprise Advanced (self-managed on-premises), and MongoDB Community Edition (free open-source). Atlas, which accounts for approximately 77% of subscription revenue, is deployed across AWS, Google Cloud, and Microsoft Azure in 130+ regions, and serves as the unified data layer combining operational, vector, and streaming data.

The platform's AI-ready architecture includes Atlas Vector Search for semantic search and retrieval-augmented generation, proprietary Voyage AI embedding and re-ranking models, LangGraph.js Long-Term Memory Store for AI agent memory, and Atlas Stream Processing for Kafka integration. MongoDB 8.3, generally available May 2026, delivers 45% faster reads and 35% faster writes over version 8.0, with optimizations targeting sub-100ms retrieval for AI production workloads. Certifications include SOC 2 Type II, HIPAA, GDPR, PCI DSS, ISO 27001, and pending FedRAMP, with compliance positioning the platform for financial services, healthcare, telecommunications, and government customers.

MongoDB operates a hybrid go-to-market combining direct enterprise field sales (largest contract exceeding $100 million) with self-serve PLG adoption via Atlas free tier and consumption-based pricing. The company reports 67,700+ enterprise customers globally, FY2026 revenue of $2.46 billion (22-23% YoY growth), and raised FY2027 guidance to $2.92-$2.96 billion. Atlas surpassed $2 billion in annual run rate at 29% YoY growth. The business achieved its first GAAP-profitable quarter in Q1 FY2026, with free cash flow of approximately $500 million TTM and 22.8% operating margin. Customer concentration spans financial services (Coinbase, Bendigo and Adelaide Bank), healthcare (Novo Nordisk, GE Healthcare, Humana), automotive (Toyota Connected), telecommunications (LG U+), retail (Victoria's Secret), and technology (Zoom, Anthropic, Hugging Face).

Name

MongoDB

Legal name

MongoDB, Inc.

Website

https://mongodb.com

Company type

Public

Founded year

2007

Operating status

Operating

Headcount range

5,001–10,000 employees

Short description

MongoDB is a publicly traded document-oriented NoSQL database platform offering MongoDB Atlas (managed multi-cloud), Enterprise Advanced (self-managed), and AI-ready capabilities including Vector Search and Voyage AI embeddings, serving 67,700+ enterprise customers across financial services, healthcare, telecommunications, retail, and government.

Ownership category

akta.pro rank

Product category

Cloud Database / NoSQL Database Software

NAICS

Software Publishers (5132), Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services (5182)

SIC

Services-Prepackaged Software (7372)

akta.pro primary industry

Database-as-a-Service (DBaaS) Platforms (HDAEAAAN)

akta.pro secondary industries

Multi-Model Databases (HDAEAAAL), Data Lake Platforms (HDAEABAC), Managed Databases (Relational/NoSQL/In-Memory DBaaS) (HDABAAAE)

Keywords

• NoSQL database
• Cloud database platform
• Document database
• Vector search database
• AI-ready data platform

Headquarters

HQ city

New York

HQ country

United States

HQ region

North America

Offices3 records

Markets served

GTM type

B2B

Offering type

Software

Cost components

Technology or R&D, Personnel, Marketing or Sales, Infrastructure, Operations

Revenue model

1. MongoDB Atlas Cloud Database: Fully managed multi-cloud database service accounting for approximately 77% of subscription revenue. Revenue is consumption-based (pay-as-you-go) aligned with cloud economics, allowing customers to pay based on actual usage. The platform offers 29% year-over-year growth with Atlas now exceeding $2 billion annual run rate.
2. Enterprise Advanced Licenses: Self-managed database licensing for enterprises running MongoDB on-premises or in private cloud environments. Revenue recognized as subscription with annual or multi-year contract terms.
3. Professional Services & Support: Implementation support, training, and consulting services alongside standard support contracts. Contributes to overall revenue mix with services often bundled in enterprise agreements.
4. Community & Academic Programs: Free Community Edition and educational licensing that drives developer adoption and future commercial conversions through the MongoDB University ecosystem.

Pricing tiers

Go-to-market motion3 records

Distribution channels5 records

Marketing channels6 records

Core offering

MongoDB fundamentally sells a document-oriented NoSQL database platform offered as a fully managed multi-cloud service (MongoDB Atlas) and as self-managed software (Enterprise Advanced and Community Edition). The Atlas platform unifies operational document storage, native vector search, full-text search, stream processing, and analytics, with Voyage AI-powered automated embeddings and a LangGraph.js long-term memory store for production AI agent workloads. The company monetizes primarily through consumption-based Atlas cloud subscriptions and recurring Enterprise Advanced licenses.

Product overview

MongoDB is a modern data platform company offering a document-oriented NoSQL database as both a fully managed cloud service (MongoDB Atlas) and self-managed software (Enterprise Advanced, Community Edition). The core platform is MongoDB Atlas, which accounts for the large majority of subscription revenue and serves over 65,200 customers. Atlas is an AI-ready developer data platform that unifies operational data, vector search, full-text search, stream processing, and analytics in a single cloud-native service deployable across AWS, Google Cloud, and Microsoft Azure. Key add-on modules include Atlas Vector Search (powered by Voyage AI embedding models) for semantic search and RAG, Atlas Search for full-text search, Atlas Stream Processing for Kafka integration, and the LangGraph.js Long-Term Memory Store for AI agent memory. MongoDB 8.3 is the current generally available database version (May 2026), delivering 45% faster reads and 35% faster writes for AI production workloads. Self-managed options include Enterprise Advanced for on-premises deployments and Community Edition for free local development. Developer tools include MongoDB Compass (GUI) and Relational Migrator. The platform is positioned as the data backend for AI agents, supporting sub-100ms retrieval, persistent cross-conversation memory, and multi-cloud deployment with 130+ global regions.

Differentiator

Problem solved

Functional benefit

Brands

• MongoDB Atlas: Cloud-hosted multi-cloud database service, the company's flagship cloud platform accounting for the majority of subscription revenue
• MongoDB 8.3
• Enterprise Advanced
• Community Edition
• MongoDB Compass
• Relational Migrator
• Voyage AI
• Atlas Vector Search
• LangGraph.js Long-Term Memory Store

Products and services

• MongoDB Atlas Fully managed, cloud-native developer data platform that provides multi-cloud database deployment, vector search, text search, stream processing, and analytical capabilities across AWS, Google Cloud, and Microsoft Azure in 130+ regions. Serves over 65,200 customers including Fortune 100 companies, generating the majority of MongoDB revenue through consumption-based subscriptions.
• Atlas Vector Search Native vector search capability within MongoDB Atlas that enables semantic search, retrieval-augmented generation (RAG), recommendation engines, Q&A systems, anomaly detection, and generative AI context. Stores vector embeddings alongside operational data and metadata in a single document model, eliminating the need for a separate vector database. Includes automated Voyage AI embeddings (public preview) for real-time embedding generation.
• Voyage AI State-of-the-art embedding models and re-rankers acquired by MongoDB in February 2025, providing automated vector embedding generation for building, scaling, and deploying intelligent applications. Powers semantic search and RAG capabilities for enterprise AI applications within the Atlas platform.
• MongoDB Enterprise Advanced Self-managed MongoDB deployment option for enterprises that want to run and manage MongoDB on-premises or in private cloud environments. Includes advanced security, authentication, and enterprise management features, competing with Atlas for regulated-industry and government customers requiring on-premises or hybrid deployments.
• MongoDB Community Edition Free, open-source MongoDB distribution for local development and evaluation. Provides the core MongoDB database functionality without enterprise management features, allowing developers to explore and experiment with MongoDB at no cost. Drives developer adoption and future commercial conversions.
• Atlas Stream Processing Stream processing capability that unifies the developer experience for working with high-velocity data streams from Apache Kafka and other sources, using the same MongoDB Aggregation Pipeline stages used for database queries. Enables real-time event-driven applications that react and respond in near real-time.
• Atlas Search Full-text search engine integrated into MongoDB Atlas, combining database, search engine, and sync mechanisms into one platform to deliver 30%-50% faster search results compared to separate implementations. Supports catalog and content search, in-app search, and single-view applications.
• Atlas Database Multi-cloud operational database service within the Atlas platform, providing the core document database with automatic scaling, built-in security, and cross-cloud replication. The foundational service upon which Atlas Vector Search, Atlas Search, and other AI capabilities are built.
• MongoDB Compass Graphical user interface (GUI) for working with MongoDB data, enabling developers and DBAs to explore, query, and manage MongoDB databases visually without command-line interaction. Available for all MongoDB deployments including Atlas and self-managed instances.
• MongoDB Relational Migrator Migration tool that helps organizations confidently migrate from relational databases (SQL) to MongoDB, including schema analysis, mapping recommendations, and guided migration workflows. Part of MongoDB's application modernization toolkit.
• MongoDB 8.3 Fourth major release of MongoDB in 19 months, generally available May 7, 2026. Delivers 35% more writes, 45% more reads, 15% more ACID transactions, and 30% more complex operations over MongoDB 8.0 without requiring application code changes. Built specifically for sub-100ms retrieval and zero-downtime AI production workloads.
• MongoDB AI-Powered Application Modernization Platform AI-powered application transformation platform launched in September 2025, combining MongoDB's NoSQL database with generative AI for automated data modeling and code transformation. Targets enterprises reducing technical debt and modernizing legacy applications.

Quantifiable outcome

• CSR creation reduced from 12 weeks to 10 minutes with Gen AI
• +4 more outcomes

Named customers11 records

Segments8 records

Ideal customer profiles4 records

Technology focussed Yes

API detail

Has API

Yes

API docs

API detail

Core technology

AI maturity

App detail

Integration6 records

AI capability7 records

Feature7 records

Partnerships

Twelve partnerships are on record, tiered core and notable.

• LangChaincoreStrategic or Co-development Partner · 28 May 2026Strategic partnership formalized to make MongoDB Atlas the premier backend for production-ready AI agents. Includes LangGraph.js Long-Term Memory Store integration enabling persistent cross-conversation agent memory and deep orchestration framework integration.
• IBM (Sovereign Core Ecosystem)notableTechnology or Integration · 5 May 2026MongoDB participates in IBM Sovereign Core ecosystem partnership supporting regulated regions with data sovereignty requirements. Specific focus on India where local compliance requirements like DPDP are being addressed.
• LG UplusnotableTechnology or Integration · 23 April 2026LG Uplus partnered with MongoDB to enhance AI-driven customer service capabilities, leveraging MongoDB for vector and operational data management.
• NutanixnotableTechnology or Integration · 7 April 2026Certified integration between Nutanix Database Service (NDB) and MongoDB Ops Manager enables automated provisioning, point-in-time recovery, and operational visibility for enterprise MongoDB deployments. Available now in NDB 2.10.
• Amazon Web Services (AWS)coreTechnology or IntegrationMongoDB Atlas is natively integrated with AWS and available on AWS Marketplace, enabling AI developers to deploy database services through AWS procurement. The partnership includes cross-region connectivity for AWS PrivateLink for secure database traffic without public internet exposure.
• Google CloudcoreTechnology or IntegrationMongoDB Atlas available on Google Cloud Platform with multi-cloud support enabling deployments across 130+ regions. Part of broader technology partnership for AI data platform capabilities.
• Microsoft AzurecoreTechnology or IntegrationMongoDB Atlas available on Microsoft Azure with full multi-cloud deployment support. Part of technology partnership enabling enterprise customers flexibility across hyperscalers.
• DatabricksnotableTechnology or IntegrationEcosystem integration between MongoDB and Databricks for unified data and analytics workflows. Customers can connect Atlas data with Databricks lakehouse platform.
• ConfluentnotableTechnology or IntegrationMongoDB integrates with Confluent's Kafka ecosystem for stream processing capabilities, enabling event-driven applications and real-time data pipelines.
• AccenturenotableImplementation/ SI/ Consulting PartnerAccenture leverages MongoDB for enterprise database modernization and digital transformation projects, implementing MongoDB solutions for clients across industries.
• TCS (Tata Consultancy Services)notableImplementation/ SI/ Consulting PartnerTCS implements MongoDB solutions for enterprise customers as part of digital transformation engagements, leveraging MongoDB for modernization projects.
• CoherenotableTechnology or IntegrationCohere embedding models integration with MongoDB Atlas Vector Search for enhanced AI retrieval capabilities and semantic search functionality.

Scale indicators13 records

Recent moves7 records

Expansion highlights6 records

Direct peers

• Couchbase: Couchbase is the closest direct competitor, offering a document-oriented NoSQL database with both self-managed and managed cloud (Capella) deployment options. It targets the same enterprise developers and AI workloads as MongoDB Atlas, including vector search for generative AI applications.
• DataStax (Astra DB): DataStax provides a managed Apache Cassandra-based NoSQL database (Astra DB) with vector search capabilities, competing for the same enterprise AI and large-scale operational workloads as MongoDB Atlas. It targets similar real-time, high-throughput use cases.

Broad incumbents

• Amazon Web Services (DocumentDB): AWS DocumentDB is a managed document database service with MongoDB-API compatibility, deeply integrated into the AWS ecosystem. It competes with MongoDB Atlas specifically on AWS while AWS simultaneously distributes Atlas via AWS Marketplace, creating a co-opetitive relationship.
• Microsoft Azure (Cosmos DB): Azure Cosmos DB is Microsoft's globally distributed multi-model database service with MongoDB-API compatibility. It competes directly with MongoDB Atlas on Azure and is bundled into Microsoft's enterprise agreements.
• Google Cloud (Firestore / AlloyDB): Google Cloud's Firestore and AlloyDB for MongoDB compatibility target the same document database workloads as MongoDB Atlas on GCP. Google's broader AI/Vertex stack creates both partnership opportunities and competitive overlap.
• Snowflake: Snowflake is a cloud data platform that increasingly overlaps with MongoDB Atlas in the unified data platform and AI workload space, including support for AI/ML and vector-style retrieval use cases. It represents a different architectural starting point but competes for the same enterprise data platform budget.
• Databricks: Databricks offers a lakehouse and AI/ML platform with vector search (Mosaic AI Vector Search) that competes for the unified data and AI workloads MongoDB Atlas is targeting. It is both a Databricks integration partner and an emerging competitor for AI data infrastructure budgets.

Emerging players

• Redis Ltd: Redis offers managed in-memory NoSQL data stores with vector search (Redis Vector Library) targeting AI applications. It overlaps with MongoDB Atlas in low-latency operational data and emerging AI retrieval use cases, though its core architecture differs.
• Elastic: Elastic provides search and observability capabilities with vector search and Elasticsearch-based document storage, competing with MongoDB's Atlas Search and Vector Search products. It is an emerging competitor specifically for AI search and retrieval workloads.

Others

• Confluent: Confluent is the primary streaming data platform partner for MongoDB Atlas Stream Processing. While not a direct database competitor, it is an adjacent infrastructure layer that increasingly bundles operational and streaming capabilities, making it an ecosystem peer rather than a head-to-head rival.

Market position

Strengths5 records

Weaknesses5 records

Competitive moat5 records

Key risks6 records

Key highlights7 records

Customer concentration

• GitHubgithub.com/mongodb
• LinkedInlinkedin.com/company/mongodbinc
• Xx.com/mongodb
• Facebookfacebook.com/mongodb

Compliance8 records

Revenue estimate

Valuation estimate

Number of profiles

Profiles15 records

Subsidiaries2 records

Funding overview

Funding rounds14 records

Investors19 records

Funding detail is available on the Subscription and Enterprise plan.Contact sales →

M&A5 records

Investments5 records

M&A and investment is available on the Subscription and Enterprise plan.Contact sales →

Frequently asked questions about MongoDB