MongoDB, Inc.
Information Technology · Systems Software
Structural read: document database incumbent transitioning from on-prem license model to Atlas consumption (~70% of revenue) on AWS/Azure/GCP. Vector Search positions MDB as a default data layer for RAG/agentic apps - competing with $PG (pgvector), Pinecone, $ESTC, $SNOW Cortex.
Developer-led GTM (community → paid) gives durable bottom-up adoption.
- Atlas growth ~30%+ Y/Y with net retention historically 120%+
- Vector Search bundled in Atlas - no separate vector DB needed for RAG
- Multi-cloud lock-in lower than hyperscaler-native DBs ($AWS DynamoDB, $GOOGL Spanner)
- Free-tier funnel + 50k+ Atlas customers seed enterprise expansion
- AI-app workloads structurally favor flexible-schema document model over rigid SQL
- Consumption model exposes revenue to customer cost-optimization cycles
- $PG + pgvector is a credible free alternative for vector workloads
- Hyperscalers ($MSFT Cosmos DB, $AMZN DocumentDB) bundle competing document DBs
- Margin compression as Atlas (lower gross margin than EA licenses) mixes higher
- Macro/IT-budget sensitivity - workload growth slowed mid-2025 before reaccelerating
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