![]() ![]() Adding or deleting as the mood or time takes you. CLZ Music is very flexible - you can enter as much or as little data as you want about your collection. The plugin would be a premium service extension and users would be responsible for their own data storage and bandwidth costs with their chosen datastore provider.I have been using CLZ Music for a couple of years now - and it’s brilliant! Like others, I wanted a way to organise my music collection - Vinyl, CD and digitised.As the user moves through the dataset, records would paginate to provide viewing access, shifting the relevant “window” as needed.The plugin would automatically cache into and out of Airtable’s current datastore records that are immediately relevant.Imagine a plugin architecture that allows you to select arbitrary database back ends like Firebase, or ElasticSearch.I hate to crap all over customer requirements that are generally reasonable and helpful to a growing product, so I’ll toss this idea out because I’ve actually mimicked this with a one-million record data set. They can’t because they support millions of records. Have you noticed that most databases that scale do not look or feel like Airtable? If you think the technical complexities are challenging, try getting every user to agree to this new product definition. As such, users must be willing to give up some features and work differently, ergo - there’s a good probability that it won’t be Airtable as you know it.Īs such, feel free to indicate here (to help the Airtable design team) understand the central and bare minimum UI and UX features that you cannot live without in a product that has vastly more scale. If you want to push the record limit to 100,000, or a perhaps a million records, something – perhaps many things – about the product experience need to change. ![]() And depending on the number of fields, especially formula fields, the practical ceiling is dynamically lower than 50,000 records. The user experience and features represent what we know Airtable to be for use cases under 50,000 records. My mostly uninformed technical assessment is that – all things constant – neither 5 million cells or 50,000 records will ever be performant given today’s commonly available consumer devices.Īnd, so what do I mean by “all things constant” in this assessment? What does that indicate? It tells me that the tipping point is not likely the underlying architecture rather, it’s the limitation of the underlying compute stack typically employed. Given the current Airtable experience and features, they’re sort’a in a box not unlike the box Google Sheets finds itself in.Ī Google sheet with 5 million cells (populated or not) looks and feels a lot like Airtable with 50,000 records. Indeed, products evolve in many ways but typically only in ways that they can actually evolve practically. I think they really have to look at how many of their customers are needing to scaling there product. I recognize the ease of airtable and its intended audience… but products do evolve. It’s not trival to do this, but it does make for a very useful solution combining the best of three very nice environments. ![]() While Airtable’s block charting features are useful in narrow use cases at the edge, analytics that blend data from many activities including Airtable and other data systems require Kibana (the ElasticSearch analytics platform) which is able to deliver broad business analytics at scale.Īll of this, of course, requires a comprehensive middle-ware that tightly integrates ElasticSearch and Airtable using their respective APIs. I even make it possible to push the data back into ElasticSearch as updates to the master data set - a basic “commit” of sorts. I have a number of tools that make it easy for Airtable users to “request” data from ElasticSearch by simply completing an Airtable form which kicks off a process that instantiates the data they need for a specific process or analytical task. I tend to combine ElasticSearch with Airtable when scale is critical and especially when pervasive search and business analytics are needed. These are all the things that ElasticSearch (for example) does poorly. It is ideal for operational processes, workflows, and day-to-day data-intensive activities especially when it comes to collecting data from other workers. My clients recognize this limitation (mostly because I’ve educated them) and they also recognize the advantages of Airtable. That said, it is certainly not the best place to store data-at-rest, or even data per-se. However, it doesn’t scale well - at least not in terms of record counts that are likely to expand well beyond the base limit. Any users run into the 50,000 limit have a work around?Īirtable has many good reasons to put it and certain data in front of business users. ![]()
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