Data storage *

Hello, my name is Andrey Sergeyev and I work as a Head of IoT Solution Development at Mail.ru Cloud Solutions. We all know there is no such thing as a universal database. Especially when the task is to build an IoT platform that would be capable of processing millions of events from various sensors in near real-time.

Our product Mail.ru IoT Platform started as a Tarantool-based prototype. I’m going to tell you about our journey, the problems we faced and the solutions we found. I will also show you a current architecture for the modern Industrial Internet of Things platform. In this article we will look into:

• our requirements for the database, universal solutions, and the CAP theorem
• whether the database + application server in one approach is a silver bullet
• the evolution of the platform and the databases used in it
• the number of Tarantools we use and how we came to this

Fast SSDs are getting cheaper every year, but they are still smaller and more expensive than traditional HDD drives. But HDDs have much higher latency and are easily saturated. However, we want to achieve low latency for the storage system, and a high capacity too. There’s a well-known practice of optimizing performance for big and slow devices — caching. As most of the data on a disk is not accessed most of the time but some percentage of it is accessed frequently, we can achieve a higher quality of service by using a small cache.

Server hardware and operating systems have a lot of caches working on different levels. Linux has a page cache for block devices, a dirent cache and an inode cache on the filesystem layer. Disks have their own cache inside. CPUs have caches. So, why not add one more persistent cache layer for a slow disk?

In 2017, we won the competition for the development of the transaction core for Alfa-Bank's investment business and started working at once. (Vladimir Drynkin, Development Team Lead for Alfa-Bank's Investment Business Transaction Core, spoke about the investment business core at HighLoad++ 2018.) This system was supposed to aggregate transaction data in different formats from various sources, unify the data, save it, and provide access to it.

In the process of development, the system evolved and extended its functions. At some point, we realized that we created something much more than just application software designed for a well-defined scope of tasks: we created a system for building distributed applications with persistent storage. Our experience served as a basis for the new product, Tarantool Data Grid (TDG).

I want to talk about TDG architecture and the solutions that we worked out during the development. I will introduce the basic functions and show how our product could become the basis for building turnkey solutions.