We’re planning to integrate Airtable with our cloud-based data warehouse. The end-user should be able to use Airtable to dynamically setup and schedule data transfer to and from our data warehouse. Data transfer should be seamless and should support 20,000+ rows. Is this technically feasible? Thank you.
Yep, I fully understand this requirement and I actually have a few clients doing exactly this with Firebase and ElasticSearch. The challenge, of course, is crafting a UX that helps users in a timely manner. While Airtable’s API is pretty good, the right solution that puts smiles on users’ faces must be carefully crafted.
I have one implementation that simulates Airtable access to about 10m Firebase nodes. As users select specific customer records, nodes associated with that customer are accessible with a simple button click.
I believe it is and it’s a simple matter of understanding the data and user requirements to build something that’s fast and efficient.
In this discussion, I raise the issue of native Airtable records capable of supporting large numbers of records as JSON objects. You might also find this interesting and perhaps a hybrid of native Airtable JSON collections combined with your data warehouse integration might be helpful to meet your objectives.
Hi Bill, Thanks for your reply. This seems a pretty daunting task haha, but this was all noted. Also, the example that you have given is kind of similar to our problem, we’ll further look into this. Thanks a lot!
You can also perform this integration using the Skyvia platform. It is a no-code tool that supports near real-time synchronization, ETL and ELT processes.
