StitchDB vs MongoDB Atlas: Postgres or MongoDB for Your App?

MongoDB Atlas vs Postgres is first a database choice and second a platform choice. Atlas is a managed MongoDB service: flexible documents, a rich query and aggregation language, and horizontal scaling through sharding, in clouds and regions worldwide. StitchDB is a managed Postgres platform: relational tables with jsonb for flexible fields, plus Auth, REST and GraphQL APIs, Realtime, Storage and functions in the same project. Since MongoDB deprecated Atlas App Services features (the Data API, Device Sync, the Device SDKs and App Services auth), Atlas is mainly a database you put behind your own API, while StitchDB includes that app layer.

#Comparison

Atlas figures are from mongodb.com/pricing; StitchDB's from pricing.

#Documents vs tables, in practice

Take an order with line items. In MongoDB you embed the items:

db.orders.insertOne({
  userId: 'u_123',
  status: 'open',
  items: [{ sku: 'A-1', qty: 2, price: 9.5 }, { sku: 'B-7', qty: 1, price: 24 }],
  createdAt: new Date(),
})

db.orders.find({ status: 'open', 'items.sku': 'A-1' })

In Postgres you can do the same with jsonb:

create table public.orders (
  id uuid primary key default gen_random_uuid(),
  user_id uuid not null references auth.users,
  status text not null,
  items jsonb not null,
  created_at timestamptz not null default now()
);
create index on public.orders using gin (items jsonb_path_ops);

select id from public.orders
where status = 'open' and items @> '[{"sku": "A-1"}]';

Or normalize the items into their own table when you need to report on them, enforce that every SKU exists, or update one item without rewriting the document:

select p.name, sum(i.qty) as units
from public.order_items i join public.products p on p.sku = i.sku
where i.created_at > now() - interval '30 days'
group by p.name order by units desc limit 10;

Postgres lets you mix both styles in one schema. MongoDB's strength is that the document model is the default and the aggregation pipeline is very expressive for nested data.

#The app layer is the bigger difference

For a database behind your own server, both are excellent. For a backend that browsers and mobile apps talk to directly, the picture changed. MongoDB's deprecation page lists the Data API and HTTPS Endpoints, Device Sync, the Device SDKs, App Services authentication and Data Access Permissions as deprecated, while database Triggers and their Functions continue. Building on Atlas now usually means adding your own API service and an auth provider.

A StitchDB project includes that layer:

• API: every table and view is a REST endpoint; GraphQL at /graphql/v1.
• Access rules: row level security policies enforced by the database for REST, GraphQL, Realtime and Storage.
• Auth: passwords, magic links, OAuth, phone, passkeys, SAML SSO, MFA, anonymous users.
• Sync: offline sync for chosen tables in the JS, Flutter, Swift and Kotlin SDKs.
• Server code: Deno Edge Functions, triggers, cron and queues.

// Directly from the browser, filtered by RLS to the signed-in user
const { data } = await stitchdb
  .from('orders')
  .select('id, status, items, created_at')
  .eq('status', 'open')

#Scaling

Atlas can shard a collection across many machines, which is the right tool for very large write-heavy datasets. Dedicated clusters scale from M10 upwards.

StitchDB scales vertically and with read copies: plans raise limits, read replicas serve REST reads closer to users and take load off the primary, and higher plans can move projects to a dedicated server without changing URLs or keys. For very large tables there is native partitioning with pg_partman. It does not shard one database across servers. If you expect tens of terabytes of hot, write-heavy data, Atlas's sharding is a real advantage.

#Search and AI

StitchDB has built-in full-text and semantic search over your tables with RLS applied, and the vector extension (pgvector) for embeddings in SQL. Atlas has its own search and vector offerings; compare them on the MongoDB docs if they are central to your app.

#Backups and portability

Atlas's pricing page says backup services are not available on the free M0 tier; check the backup options of the paid tier you pick. StitchDB includes point-in-time recovery on every plan (24 hours on Free, 7 days on Pro, 14 on Scale, 30 on Enterprise) and a full project export as a pg_dump plus users and files. Both databases are open formats with standard tools (mongodump, pg_dump), so neither traps your data.

#Working with each day to day

Atlas gives you Compass, the MongoDB shell, drivers for every major language and a web UI for collections, indexes and performance. Schema changes are usually code changes: you start writing a new field and backfill old documents when needed.

StitchDB gives you Studio (table editor, SQL editor, policies, users, files, advisors), the stitchdb CLI with SQL migration files and local development, and generated types. Schema changes are migrations; before one runs, StitchDB tells you which tables it locks and for how long given their size, and offers a version that keeps the app running. Any Postgres GUI, ORM or BI tool also connects directly over TLS.

The practical difference: on Atlas, data shape is enforced by your application code; on Postgres, it is enforced by the database, which matters more as more apps and people write to the same data.

#Trade-offs to weigh

• StitchDB is EU-only, younger, and has no self-hosted edition. Moving from MongoDB means rewriting queries in SQL.
• Atlas leaves you to build the API, auth and sync layers yourself after the App Services deprecations, and flexible schemas push validation into app code.

#Which should you pick?

Pick MongoDB Atlas if your data is deeply nested and read as whole documents, you need sharding at large scale, your team knows MongoDB well, or you need regions worldwide and already run your own API.

Pick StitchDB if your data is relational, you want the app layer (auth, APIs, realtime, storage, sync) included, you like SQL for reporting, and your users are mainly in Europe.

For more options see MongoDB Atlas alternatives and SQL vs NoSQL for mobile and web apps.

#FAQ

#Is Postgres good at JSON?

Yes. jsonb stores JSON in a binary format with GIN indexes and operators such as @>, -> and ->>, so you can query inside documents efficiently.

#Is MongoDB Atlas still a good choice in 2026?

As a managed database, yes. The deprecations affect App Services features, not the Atlas database.

#Can I move data from Atlas to StitchDB?

Yes, with a manual migration: export collections with mongoexport, load them into staging jsonb tables, then reshape them with SQL. There is no automatic MongoDB importer.

#Which is cheaper?

At small sizes both are free. As of November 2026, Atlas Flex is capped at $30/month for 5 GB, and StitchDB Pro is $15.99/month for a 10 GB database plus auth, storage and APIs.

Get Postgres with the app layer built in: start a free StitchDB project.