Sure - you can do most things yourself - doing analytics is actually pretty hard to get right. From my pov, their value is on not having to do it yourself, plus a good, flexible API.
Sure I get using existing tools but I'm trying to grasp the real value here. So I should view it as an analytics platform that supports completely adhoc data types? Because, to me, the first main selling points it makes on their site I couldn't care less about. Storing and querying adhoc data is a solved issue and extremely easy.
Now if they are providing the tools to make analysis quick, efficient, and intelligent - That makes a bit more sense. Guess I'll have to check out a trial.
[note: I work at Keen and have a lot of biases :)]
The main alternative to Keen IO is to build your own backend. Some developers will always prefer that, but many folks don't have the time & resources to devote to constructing & maintaining an analytics backend. Here are some things that people appreciate about Keen IO:
- The ability to start collecting & querying their event data immediately & easily
- Keen's uptime and reliability (transferring backend ops from their pager to ours).
- Not having to worry about scalability. For customers who are collecting billions of events per month and planning to double in less than a year, data challenges are less trivial.
- A point and click query interface that can be used by some non-devs to run analysis, create graphs, extract data, etc
- Query & visualization libraries that allow you to create reporting interfaces (websites/dashboards/customer-facing-analytics) much more quickly
- A growing inventory of features & open source tools that build on the API (scoped keys, caching, notifications, dashboard templates, etc)
Our thesis is that storing and analyzing ad hoc data is not a solved problem -- while it may be pretty easy at some scales, it is rather hard at others.
Keen IO takes an API-based approach to the problem, which means:
- developer abstractions are higher level than rolling your own
- scalability is as easy as "my bill went up" (as opposed to "my ALTER statements stopped working!" or "I need to leave mongo and buy a book on distributed system engineering!"
- ability to cover new/emergent use cases is a lot higher than you would get with an off-the-shelf analytics product
