| Feature | jsondb.cloud | MongoDB Atlas |
|---|---|---|
| Setup time | 1 minute | 30+ minutes |
| Connection management | Pure HTTP | Drivers + connection pooling |
| Pricing | $9/mo flat | Cluster size + IOPS + bandwidth |
| Free tier | 1,000 docs | 512 MB shared cluster |
| Edge distribution | 150+ nodes | Specific cloud regions |
| Querying | URL params | MQL (MongoDB Query Language) |
| Aggregation pipeline | No | Yes |
| Transactions | No | Yes |
| Full-text search | No | Atlas Search |
| Change streams | No | Yes |
| Webhooks | Yes | Atlas Triggers |
| Ops overhead | None | Cluster management |
| Version history | 5-50 versions | No |
| CLI tool | Yes | mongosh |
Why jsondb.cloud: Zero Setup, Zero Ops
MongoDB Atlas requires cluster provisioning (choose a tier, region, and configuration), connection string setup, driver installation, and connection pool management. You need to understand replica sets, read preferences, and write concerns.
jsondb.cloud requires one API key and one HTTP call. No clusters, no connection strings, no drivers. The infrastructure is invisible.
Why jsondb.cloud: No Connection Management
MongoDB drivers maintain persistent connections with connection pooling. In serverless environments (Vercel, Netlify, Cloudflare Workers), this creates cold start issues and connection exhaustion.
jsondb.cloud is a pure HTTP REST API. Every request is stateless. No connections to manage, no cold start penalties, no connection pool tuning.
Why jsondb.cloud: Edge-Native Performance
jsondb.cloud serves data from 150+ global edge nodes with sub-20ms latency. MongoDB Atlas runs in specific cloud regions — you choose one, and users far from that region get higher latency. Global clusters exist on Atlas, but they require an expensive dedicated tier.
Why jsondb.cloud: Simple, Flat Pricing
MongoDB Atlas pricing depends on cluster tier, storage, IOPS, data transfer, and optional features like Atlas Search and Analytics. It's powerful but complex to predict.
jsondb.cloud is $9/mo flat for Pro. No calculator required.
Why jsondb.cloud: No Ops Overhead
MongoDB Atlas is "managed" but not ops-free. You still deal with: cluster upgrades, scaling decisions, index optimization, backup schedules, and monitoring. jsondb.cloud has zero ops. No clusters to scale, no indexes to manage, no backups to configure.
Fair Comparison
MongoDB Atlas is vastly more powerful: aggregation pipeline, transactions, full-text search, change streams, and 20+ years of battle-tested storage. If your data is complex or large-scale, use Atlas. jsondb.cloud is for when MongoDB is more database than you need.
Code Comparison
// Connect and store data in MongoDB Atlas
import { MongoClient } from 'mongodb';
const client = new MongoClient(
'mongodb+srv://user:[email protected]'
);
await client.connect();
const db = client.db('myapp');
await db.collection('users').insertOne({
name: 'Alice',
status: 'active',
});
// Query
const users = await db.collection('users')
.find({ status: 'active' })
.sort({ createdAt: -1 })
.limit(10)
.toArray();
await client.close();// Store data in jsondb.cloud
// No connection. Just HTTP.
fetch('https://api.jsondb.cloud/v1/db/default/users', {
method: 'POST',
headers: {
'Authorization': 'Bearer <YOUR_KEY>',
'Content-Type': 'application/json',
},
body: JSON.stringify({
name: 'Alice',
status: 'active',
}),
});
// Query with URL params
fetch('https://api.jsondb.cloud/v1/db/default/users?filter[status]=active&sort=-createdAt&limit=10', {
headers: { 'Authorization': 'Bearer <YOUR_KEY>' },
});Ready to simplify your document database?
Import your existing data in seconds with our CLI:
npx @jsondb-cloud/cli push export.json --to my-collection