From what I've seen, each solution has been pretty specific to the situation. I've rarely seen one tech stack prevail at low to reasonable scale. At reasonable

From what I've seen, each solution has been pretty specific to the situation. I've rarely seen one tech stack prevail at low to reasonable scale. At reasonable scale, I've seen people get really far with pure graphite setups by utilizing tools like [carbon-c-relay](https://github.com/grobian/carbon-c-relay https://github.com/grobian/carbon-c-relay), [carbonate](https://github.com/graphite-project/carbonate https://github.com/graphite-project/carbonate), and high integrity filesystems like zfs underneath. It's a very hands on operation though. Things like growing the cluster are hard to do without downtime. If constant growth and uptime is a concern, something like openTSDB might be a great choice. The complexity of setting up a Hadoop + HBase cluster is a pretty big upfront cost, but man is this thing the cockroach of time series data stores. Adding storage is just growing the HBase cluster. Querying across years of data is pretty simple and straightforward. For the complexity involved, openTSDB is worth it.