Ignite can store the whole data set on disk and X% in RAM thanks to the native persistence. So, you decide how much data you'd like to keep in RAM: https://ignite.apache.org/arch/memorycentric.html
As per times series, I heard that Ignite is being used for that use case. However, you might need more. My suggestion is to start and see how it goes. -- Denis On Tue, Nov 6, 2018 at 4:05 AM Mikhail <[email protected]> wrote: > Hi Igniters, > > Are there any best practices of storing time series > data in Ignite? We need it for extremely high load IoT system. Cassandra is > likely to be an appropriate solution, but slow speed of analytical SQL > queries are not acceptable for us. We can implement Ignite over Cassandra, > but we need to access the hole data in Ignite and the cache shouldn't be > extremely huge (e.g. it should be cache per day). > We want to have the similar approach, as for example in > [1]. However, writing such functionality from scratch has a lot of > pitfalls. Are there any out-of-the-box features for time series data in > Ignite? Does it sound reasonable to implement rollover pattern in Ignite > (like in ES)? Or there could be another options? > > [1] - https://www.elastic.co/blog/managing-time-based-indices-efficiently > > -- > Best Regards, > Mikhail
