Memory-Efficient Indices for In-Memory Storages
Most databases implement indices as a kind of tree. I will show you that columnar storages can do even better. (mehr …)
How In-Memory Compression Affects Performance
Modern computers are fast. So fast that there is a huge gap between computing speed and memory bandwith and latency in memory-heavvy applications. (mehr …)
How to balance a database between OLAP and OLTP workflows
In this blog article, we will be comparing OLAP (Online Analytical Processing) and OLTP (Online Transaction Processing) databases. We will discuss their differences and similarities, discuss the ideal database architecture for a database that can handle both OLAP and OLTP workloads, and provide a synthesis of the two. By the end of this article, you will have a better understanding…
Designing a programming language for distributed systems and highly parallel algorithms
Almost 99% of all newly invented are imperative programming languages. But imperative languages have one drawback: their parallelization is hard. (mehr …)
On designing an interface for columnar in-memory storage in golang
The advantages for columnar storages over row based storages are the ability for good in-memory compression (low memory usage) and cache locality when accessing only few columns (performance). Designing an Interface When designing an interface for a storage engine for an in-memory database, a lot of considerations have to be made. Here are the design goals: The interface must be…
