π₯οΈ So I was casually doomscrolling X (yes, again)... when I stumbled upon a post by DEV Community that made my brain short-circuit:
β¨ βScoutDB turns plain English into MongoDB queries.β
Wait, what?!
π§ The Problem
You've got the data questions, but not always the query-fu:
"Find all users who joined after Jan 2023 and liked more than 5 posts"
Normally, you'd need to hand-craft some MongoDB incantation like:
db.users.aggregate([
{ $match: { joinDate: { $gte: ISODate("2023-01-01") }, likes: { $gt: 5 } } }
])
But what if you could skip the syntax pain?
π Enter ScoutDB
ScoutDB is like having a friendly AI that:
β
Understands what you're trying to ask in English
β
Writes the MongoDB query for you
β
Visually maps relationships across your collections
β
Gives you a canvas to explore like a boss
βοΈ How It Works
You type:
Show me all posts with more than 100 likes created in the last 30 days
ScoutDB replies with:
db.posts.find({
likes: { $gt: 100 },
createdAt: { $gte: new Date(Date.now() - 30*24*60*60*1000) }
})
Then maps the results and relationships for you in a visual explorer.
No more $lookup
headaches. No more crying in JSON.
πΈ I Found It Like This
Saw this post by @ThePracticalDev on X π
(I swear MongoDB and ScoutDB logos look like they just agreed to rescue all devs from query hell)
π§ͺ TL;DR
- π£οΈ English β MongoDB query? β
- π§ Auto-maps your schema? β
- π¨ Visual canvas for data exploration? β
- π§£ Found it while doomscrolling Twitter? BIG β
- π§΅ Original Post from DEV Community
π¬ So, are you still writing $match
manually or are you letting ScoutDB take the wheel?
Tell me below π
Top comments (2)
β€οΈ thanks for writing about our product
Thank you for the shoutout! You can join our waitlist to have early access :)