Glide Big Tables is now available!

Join our Big Tables webinar on Wednesday, May 31st at 12pm ET / 9am PT :spiral_calendar:

Today, we’re thrilled to extend the scale of custom business software you can build in Glide with Big Tables, available now. :rocket:

While a normal Glide Table is limited to 25,000 rows, Big Tables can support of up 10 million rows of data so you don’t have to worry about scaling your apps.

We’re excited to launch our own high-scale data source that doesn’t require customers to set up their own database. No more worrying about provisioning, hosting, regions, or migrations. With Big Tables, you can unlock the power of a database with the simplicity and ease of Glide. Learn more about Big Tables in our recent blog.

Unlock database features from day one

Businesses are already scaling their apps with Big Tables. We’ve added charts, rollups, and full-text search so you can visualize and make sense of massive amounts of data such as inventory, sales, orders, and more.

How to get started

Big Tables is available on Business and Enterprise plans. To get started, log in and select “New Big Table” in the tables menu of the data editor. You can also import data into a new Big Table by right-clicking the data source from the tables menu, selecting import, and choosing which files you want.

We can’t wait to see how you leverage Big Tables in your projects. Please let us know if you have any questions, and also, if you’re building with Big Tables, join us in the Big Tables community to share your experience!

David

P.S. Special thanks to our Glide Experts and beta community members for the invaluable feedback and engagement throughout the beta!

31 Likes

David, just a technical curiosity: are Big Tables the same Firebase databases?

Can you tell us a bit more about their technical capabilities beyond supporting up to 10MM rows of data?

Thanks!

We’ll be publishing a technical blog post soon that goes into the implementation details of Big Tables.

10 Likes

Hey, is there a way you can convert a normal table into a big table like transfer all the data instead of having to start all over?

You can transfer the data easily enough - CSV import/export is probably the simplest method. But you’d have to recreate any computed columns and reconfigure any components that use the table. Keep in mind that not all computed column types are supported with Big Tables.

4 Likes

Thank you

Can we shine some light on these limitations with this release? Thank you.

1 Like

The docs are (almost) up to date with regards the limitations.

The only thing that’s changed since the docs were last updated is you can now do Joined Lists of non-computed columns into Glide Big Tables (this was literally released just a couple of days ago).

3 Likes

Are they planning to bring Big Tables to Classic Apps?

I seriously doubt it.

Perfect! :wink:

But The issue is, can the apps handle it ?

my apps, after 5000 more record, it seems to be laggy, and slow loading

Are these apps built on Glide Tables or a 3rd party db like Google Sheets? Also depends on what you’re doing with the data.

Big Tables are inherently faster because the calculations are done server-side, not on the device

now im using Glide Table (Glide Pro), since google sheets took a toll of usages whenver a changes occured.

i thought maybe a lot of computed column in one table could cause the lag. is that true ?

Actually, strictly speaking I don’t think this is correct :thinking:

Computed columns are still handled client-side, the main performance benefit comes from the fact that the client only has a small subset of the data at any given time, with additional data fetched as required.

And as I understand it this is why providing support for all computed column types has been a challenge. For example, the Single Value column is not supported (and probably won’t be). That makes sense when you consider that in order to calculate Single Value → Average (for example), the client would need simultaneous access to the entire dataset - which it doesn’t have.

3 Likes

can i assume if the more computed column, the more resource need to be run in client devices ?
thats what make the app run slow ?