Tarantool is an OpenSource in-memory database with features you would expect from traditinoal DBMS: primary and secondary indexes, synchronous replication, transactions and sharding. It has high programmability end extensibility thanks to embedded LuaJIT.
Often in-memory databases and data grids are hard to use because they force developers to write code in compiled languages and go through complex delivery cycle.
We believe that there is a reason why Lambda architecture and FaaS in general became so successful. So we would like to talk about our product (Tarantool Data Grid) that takes ideas from in-memory data grids and FaaS and combines them together to reach even higher speed of innovation in places where it matters most: between modern internet applications and core business services.
Topics I would focus on:
- History and business value of Tarantool Data Grid
- Writing code close to data. How we embedded an IDE to a data grid. LSP and dynamic code reloads.
- Role-based clustering and horizontal scaling with SWIM protocol
- Scaling from one Docker container on developer's machine to a cluster with 100-s of nodes
- How to support multiple teams working with the same codebase and data inside the cluster
- Use cases from a few of our customers in retail and investment banking
