Intuitively it seems to me that the major issue with perceived slowness of large business applications (such as CRM systems) is the absence of any pre-loading / caching of data for the user.<p>In my experience most users only work on a small subset of data and work on the same or similar records and processes every day, so I'd be interested to have the application learn what subset this is for a particular user or group of users and then do 'pre-emptive' loading to increase the responsiveness of the application and improve the user experience.<p>If I want to avoid re-inventing the wheel, what are some good resources that deal with strategies on how to achieve this? What are common pitfalls?
One powerful way to deal with these problems is event sourcing. It's a reasonably elegant way to materialize a single application-specific cache based on many different data sources. Two great resources:<p><a href="https://engineering.linkedin.com/distributed-systems/log-what-every-software-engineer-should-know-about-real-time-datas-unifying" rel="nofollow">https://engineering.linkedin.com/distributed-systems/log-wha...</a><p><a href="https://queue.acm.org/detail.cfm?id=3321612" rel="nofollow">https://queue.acm.org/detail.cfm?id=3321612</a>
A good example is superhuman the email client. They cache data in the browsers local web sql database.<a href="https://en.wikipedia.org/wiki/Web_SQL_Database" rel="nofollow">https://en.wikipedia.org/wiki/Web_SQL_Database</a><p>Then all searches etc are fast, due to not having to go to the server.<p>I'm not sure how they implement that, but I would probably go with a websocket that sends the latest data to the client which then stores it in Indexed DB (the browsers local database).<p>I don't know of any solution that does this out of the box.