I have decided to go with the Database Akumuli. My reasoning behind this is both because of the index structure it uses along with it’s documentation. This data base clearly states in the README that it uses a combination of an LSM tree and B+ tree. These also happen to be trees that are very well researched and it is easy to become well informed about these trees. Other databases I’ve looked at, for example InfluxDB, while very well documented, uses it’s very own specific tree that was created specifically for this database. Therefore, it is more difficult to learn about it. Akumuli also has a page where it describes it’s index structure, https:\/\/akumuli.org\/akumuli\/2017\/04\/29\/nbplustree\/. Furthermore, I have cloned the repository and looked at the index source code. It is in C plus plus, a language I am not as familiar with, but I have used it once or twice. This code was well organized and well commented. For the index the programmers used a boost property tree. While I couldn’t find very much documentation about the property on boost, Akumuli is good at explaining the functionality of the tree. On Thursday I met with Xunfei, who gave me some helpful advice as to where to focus my efforts to be prepared for the proposal. One of these areas includes preliminary testing of the database. At this point I do not have that time at my disposal, seeing as I have just spent a lot of time and effort finding and choosing this database. This requires learning how to use the database and figuring out a testing environment along with finding datasets. Often ingesting datasets into a database can be very time consuming. However, the documentation of Akumuli does include some details and figures about it’s performance. I am in a good spot. I have a solid direction to go in. While there are still some things I need to do, I am only at the first draft stage of the proposal, so there is still time to do things and include them in my final proposal.<\/p>\n","protected":false},"excerpt":{"rendered":"