In-memory databases are not economically scalable. To a first approximation, database volume is the integral of database throughput, so databases that require extreme I/O throughput also tend to require extremely high volumes of online data. Many typical sensor data models, which drive much of the need for high-throughput I/O, grow by petabytes per day so the multiple orders of magnitude difference in media cost make DRAM storage infeasible.
If the bottleneck is not storage bandwidth, and it isn't for many recent systems and modern software architectures, then there is no practical performance advantage to keeping your data purely in-memory. This has been demonstrable ever since PCIe HBAs with arrays of cheap SSDs became practical.
If the bottleneck is not storage bandwidth, and it isn't for many recent systems and modern software architectures, then there is no practical performance advantage to keeping your data purely in-memory. This has been demonstrable ever since PCIe HBAs with arrays of cheap SSDs became practical.