Why Your React Data Tables Are a Bloated Mess (And How to Automate Them)

#typescript #react #architecture #opensource

🛑 Building data tables in B2B SaaS is the most tedious, soul-crushing task in full-stack engineering.

Every time you need a new dashboard view, your engineers do the exact same dance:

👎 1. Write 200 lines of TanStack Table frontend boilerplate.
👎 2. Manage useQuery state for pagination, sorting, and complex filtering.
👎 3. Write a backend API to parse ?column=price&sort=desc&page=2 into something the DB understands.
👎 4. Write Drizzle ORM queries to manually map those query params to SQL conditions.

If your team is doing this manually for every single table in your enterprise app, you are burning money and engineering hours on solved problems.

🔌 The Disconnect Between Client and Server

TanStack Table is a masterpiece. Drizzle ORM is a masterpiece.
But out of the box, they don't communicate.

When a user clicks "Sort by Date" on the frontend, you have to manually map that string to an orderBy: desc(invoices.date) on the backend. Multiply this by 50 tables, 10 columns each, and varying filter types (contains, equals, greater than).

💥 The Result: You end up with a massive, brittle translation layer that breaks every time a schema changes.

🛠️ The Engineering Solution: TableCraft

I got tired of watching teams waste entire sprints building standard CRUD tables. So I built an engine to eliminate the translation layer.

Meet TableCraft.

TableCraft acts as the missing bridge between Drizzle ORM and TanStack Table. Instead of writing the frontend state and the backend query logic separately, TableCraft auto-generates the APIs directly from your Drizzle schema:

✅ Filtering
✅ Sorting
✅ Pagination
✅ End-to-end type safety

You define the schema once. The engine automatically handles the REST API generation (via Hono) and the frontend table rendering (via React).

📈 Why This Matters for Scale

When you are moving fast to find Product-Market Fit (PMF), you cannot afford to spend 5 hours building a user directory table. You need to drop the schema, render the table, and move back to writing core business logic.

Stop building pagination and sorting from scratch. It is junior-level busywork.

🚀 Try it yourself

I open-sourced the engine. If you want to stop wasting your engineering team's time and enforce strict, type-safe table generation, check it out below:

👉 Fork TableCraft on GitHub (jacksonkasi1)

Build systems, not components.