Technology
MongoDB Development & Consulting Services
MongoDB engineering — schema design, indexing, aggregation pipelines, Atlas operations, and the discipline to use document storage well.
What we build with MongoDB
- Document schema design with proper embedding vs. referencing patterns
- Index strategy: compound, partial, text, and wildcard indexes
- Aggregation pipeline design for analytics-style queries
- MongoDB Atlas operations: cluster sizing, autoscaling, backups
- Sharding strategies and zone-based replication for global apps
- Migrations between MongoDB versions, providers, or to other databases
Why DiveScale
Built by engineers who ship MongoDB in production
MongoDB is the right pick when documents are the natural shape of your data — content, events, IoT readings, flexible user-generated structures. DiveScale ships MongoDB with the schema discipline most introductions skip: clear embedding rules, proper indexes, and aggregation pipelines that actually use them.
We default to MongoDB Atlas for managed operations, with proper IAM, VPC peering, and CMK on regulated workloads. Self-hosted only when very specific compliance or topology requirements rule out Atlas.
And we benchmark honestly. MongoDB is excellent for the right workloads and a poor fit for highly relational ones — we say so up front and propose Postgres when the data shape calls for it.
MongoDB use cases we deliver
How we deliver
Our MongoDB delivery process
- 01
Schema review
Embedding vs. referencing decisions, indexing strategy, and aggregation pipeline targets.
- 02
Targeted tuning
Index changes, pipeline rewrites, and connection pooling — measured wins first.
- 03
Operations + DR
Atlas autoscaling, backup verification, PITR drills, and cross-region replication.
- 04
Operate or hand off
Ongoing MongoDB-as-a-service or a clean hand-off with monitoring and runbooks.
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Learn moreMongoDB — Frequently Asked Questions
MongoDB when your data is naturally documents and the read shape matches. Postgres when relations dominate or you want a single engine for both transactional and analytical work. We pick honestly, not by trend.
