A flexible document database for unstructured or growing data.
MongoDB is a document database that handles unstructured or frequently changing data flexibly. Instead of rigid tables it stores content as interlocking documents, which leaves a lot of room to move, especially in a product's early phase. Through the aggregation pipeline you can run complex analytics right inside the database. It suits cases where the data model needs to grow quickly or do without a fixed schema.
More in the documentationWe use MongoDB when your data is nested by nature, such as product catalogues with shifting attributes or event logs without a fixed structure. You spare yourself the constant reshaping of tables and let the schema grow with the product, without triggering a migration for every new idea.
await db.collection('orders').insertOne({
customer: { name: 'Mara', vip: true },
items: [{ sku: 'A1', qty: 2 }],
});
const vips = await db.collection('orders')
.find({ 'customer.vip': true })
.toArray();Good to know
Schema freedom does not mean thinking schema-less. Settle on a deliberate document model and validate it, for instance through Mongoose, otherwise inconsistent structures quietly pile up within the same collection.
More tools we work with in the same area.
PostgreSQL
Our first choice for relational data, powerful and reliable.
MySQL & MariaDB
Proven relational databases for classic applications.
MS SQL Server
For enterprise environments and Microsoft integrations.
Supabase
Postgres with auth, storage and realtime as a backend-as-a-service.
Redis
An ultra-fast key-value store for caching and realtime features.
SQLite
An embedded, serverless database, ideal for edge and local apps.
You don't have to decide that, it's our job. Tell us about your plans.