A flexible schema
JSON / BSON documents whose structure can evolve without heavy migrations, with validation rules to keep the model under control.
Expertise · MongoDB
MongoDB Development: NoSQL Databases Modeled Around Your Use Cases
Etixio designs, optimizes and evolves your MongoDB NoSQL databases, modeling document data around your application’s reads, writes and changes. We also prepare this data for the AI use cases in your product: search, assistants and agents.
Understanding the technology
MongoDB in your project.
MongoDB is a document-oriented database. Information is organized in structures that can match an application’s reads and writes. This model requires choosing what is grouped within a document, what remains referenced elsewhere and which validation rules apply.
The benefits for your application
Why choose MongoDB?
MongoDB is well suited to semi-structured data, schemas that change often and applications that read complete objects rather than joined tables. For highly relational data with many cross-entity transactions, a database such as PostgreSQL is often still preferable.
Horizontal scaling
Replication with automatic failover and sharding to distribute data and load across multiple servers.
A rich query language
Aggregation pipeline, full-text search, geospatial queries and time series collections cover many application needs.
Developer tooling
Drivers for the main languages, MongoDB Compass to explore data and MongoDB Atlas for a managed cloud service.
What we cover
The work we take on.
Documents
Define structures, relationships and validation rules.
Access
Build indexes and aggregations based on actual queries.
Operations
Prepare backups, restoration and monitoring of behavior under load.
Our MongoDB expertise
The MongoDB ecosystem we master.
Model & queries
Embedded or referenced documents, schema validation, aggregation pipeline, change streams and multi-document transactions when consistency requires it.
Indexes & performance
Single-field, compound, text, geospatial, hashed and wildcard indexes; execution plan analysis, query profiling and WiredTiger cache tuning.
Availability & scaling
Replica sets with automatic failover, read preferences, sharding and shard key selection, MongoDB Atlas managed clusters.
Security
SCRAM or x.509 certificate authentication, role-based access control, encryption in transit and at rest, field-level encryption and audit logs.
MongoDB and AI
Data your AI features can rely on.
An assistant or agent is only as reliable as the data it queries. We structure documents, metadata and access rights so that document search, the vector search offered by MongoDB Atlas or an agent can rely on a consistent, up-to-date source. See our AI solutions for business and our BI & data offering.
In the field
From technology to real-world use.
For a catalog with variable attributes, we study the most frequent filters, searches and updates. The schema and indexes are designed from these operations. Aggregations are tested with realistic volumes, and structural changes come with a strategy for existing documents.
The choices that matter
The choices to examine before building.
A flexible structure does not mean no model. Duplication can speed up some reads while complicating updates. We review the expected consistency, the transactions required and how documents will evolve before settling on a structure.
From work to deliverables
Delivered work your team can take over.
The scope of the engagement specifies the components to build or take over and the acceptance criteria. We prepare what is needed to understand the changes, verify them and continue the work.
- Documented data model
- Migrations and integration tests
- Data access and query analysis
Frequently asked questions
MongoDB: your questions.
What is MongoDB and why use it?
MongoDB is a document-oriented NoSQL database (JSON / BSON). It suits APIs, mobile applications, IoT and products whose data model changes often, thanks to its flexible schema and horizontal scaling.
Is MongoDB suitable for enterprise applications?
Yes. Role-based access control, encryption, audit logs, replication and backups make it possible to run it in production. MongoDB Atlas offers these features as a managed service. The choice depends mainly on the nature of the data and consistency requirements.
What is the difference between MongoDB and a SQL database?
MongoDB stores documents with a flexible schema and distributes easily across multiple servers. A SQL database organizes tables linked by constraints and excels at cross-entity transactions. MongoDB suits semi-structured data, a SQL database suits highly relational data.
How do you optimize MongoDB performance?
Indexes suited to actual queries, a deliberate choice between embedded documents and references, optimized aggregation pipelines, a well-tuned connection pool, appropriate read preferences and monitoring with Compass or Atlas.
Does MongoDB support transactions?
Yes, MongoDB supports multi-document ACID transactions, including on sharded clusters. They come at a cost: a well-designed model reserves them for the operations that require them.
Should documents be embedded or referenced?
Embed data that is read together and updated atomically. Reference data that is shared, large or in many-to-many relationships, to avoid duplication. The decision depends on queries and consistency requirements.
How do you scale a MongoDB database?
Replica sets provide high availability and can distribute reads; sharding distributes data based on a well-chosen shard key. Atlas adds global clusters and automatic resource scaling.
Is MongoDB suitable for data analytics?
For operational analytics, yes, with the aggregation pipeline, MongoDB Charts and connectors to BI tools. For heavy analytics, a dedicated data warehouse remains more suitable.
Can MongoDB be used for AI features?
Yes. MongoDB can serve as a source for an assistant or an agent, and Atlas offers vector search. What matters most is the quality of documents, metadata and access rights, which we address before the production release.
What collaboration models do you offer?
A fixed-price project for a defined architecture, migration or optimization, a dedicated team to evolve the application and its data over time, or a targeted engagement (performance, Atlas, model audit).
Let’s talk about your technical context.
Tell us about the application, the issue to address and the known constraints. We will review the dependencies and the initial scope of work with your team.