I need help with updating specific rows in a table that exists inside a Notion page using their API. My goal is to find rows where the Environment column matches a certain value, then modify the Date Updated, Updated By, and Version columns for those matching rows.
I have a table embedded in my Notion page with columns for Environment, Date Updated, Updated By, and Version. I want to programmatically update these fields based on environment criteria.
I attempted this approach to query rows by Environment value:
But I think this is wrong since I’m targeting a database endpoint when my table is actually embedded within a page. What’s the proper way to filter and update table rows that live inside a page rather than being a standalone database?
Everyone’s right about the database ID vs page ID issue, but there’s a bigger problem here.
You’ll be running these updates constantly - different environments, teams, schedules. Managing curl commands and error handling gets old quick.
I hit this same issue with multiple deployment environments updating our Notion tracking tables. Started with bash scripts but it became a nightmare handling failures, retries, and team coordination.
What fixed it? Automated workflow. Our CI/CD pipeline now triggers updates automatically, filters environment rows, and updates everything in one shot. No more manual API calls or 2am debugging sessions.
Build the whole flow visually - connect to Notion, set up filtering, map updates, handle errors properly. Way more reliable than scripting it yourself.
The database ID advice still stands though. Grab it from your table’s full view URL.
Working with embedded tables through the API is frustrating at first. Those database ID extraction methods are right, but here’s something about property types that totally caught me off guard during similar updates. Check what property type your Environment column actually uses before you start filtering and updating. If it’s a Select property instead of rich text, you’ll need to structure your filter differently. Same goes for other columns you’re updating - Date properties need ISO format, People properties need user IDs, not names. I learned this the hard way when my updates kept failing silently. The API would return success but nothing changed because I was sending wrong data types. Run a simple GET request first to see your database’s actual property structure. This’ll save you hours of debugging when your filter works but updates don’t stick.
Yeah, this trips people up all the time. Those tables in Notion pages? They’re actually databases - just displayed differently.
Your API approach is right, but you need the table’s actual database ID. It’s not the same as the page ID, even though the table sits inside the page.
Grab the database ID like this:
Open the table in full page view
Copy that URL - the ID after the last slash is what you want
Or hit the API to list all databases and find yours
Once you’ve got the right database ID, your query should work fine. Then just use PATCH requests for updates.
But honestly? This gets messy real quick when you’re juggling multiple environments and doing regular updates. Been there - manual API calls turn into a maintenance nightmare.
What saved my sanity was building an automated workflow that handles the filtering, updating, and error stuff. No more fighting with curl commands or babysitting tokens.
You can build the whole thing visually - trigger it however (webhook, schedule, manual button), filter your Notion rows, update multiple fields at once. Way cleaner than scripting everything from scratch.
The issue is how Notion handles tables in pages. When you create a table inside a page, Notion automatically creates a database behind the scenes. Your API call looks right, but you’re probably using the wrong ID.
To get the right database ID for your table: right-click the table, select ‘Copy link to view’, then grab the 32-character ID from that URL. This database ID won’t match your page ID.
Once you’ve got the correct database ID, your filtering should work fine. After you get the matching rows back, you’ll need to loop through the results and send PATCH requests to update each row. Use this endpoint: ‘https://api.notion.com/v1/pages/{page_id}’ where page_id is the ID of each row from your query.
Here’s the key thing: each row in a Notion database is actually a page object. That’s why you use the pages endpoint instead of databases for updates. Also make sure your property names match exactly what’s in your database schema - capitalization matters.
had the same issue last week lol. your curl command looks good, but you need the database id, not the page id. just right-click the table and inspect element - the database id’s right there in the html. way faster than opening full view.
Yeah, the database ID mix-up is what’s killing you. Fix that first, then watch for rate limits on bulk updates. Notion only allows 3 requests per second - go faster and you’ll hit 429 errors. Learned this the hard way when half my production updates crashed.
Also check your filter syntax. If Environment’s a multi-select, use “multi_select” not “rich_text” in your filter. The property inspector shows this but it’s easy to miss.
For updates: batch them right and always check response status before moving on. Bad property formatting causes silent failures all the time.
Yeah, that terminology trips everyone up. When you make a table in Notion, you’re actually creating a database that’s embedded in the page. Here’s the thing - you need the database ID, not the page ID where your table sits. Click on your table and hit “Open as page” or use the three-dot menu to get the full database view. Grab the database ID from that URL. With the right database ID, your filtering should work fine. Just watch out - if your Environment column uses select properties instead of rich text, you’ll need to change your filter type. For updates, you’ll need separate PATCH requests for each row using the pages endpoint. Each row from your query has its own page ID for updates. Pro tip: test your query without filters first to make sure you’re hitting the right database. Once that’s working, add your filters.