Skip to main content

Show HN: SirixDB – Storing and Querying of Temporal Data (Java and Open Source) http://bit.ly/2BKvBih

Show HN: SirixDB – Storing and Querying of Temporal Data (Java and Open Source) I'm developing a storage system for versioning data at the subfile level, especially well suited for SSDs due to its log-structured COW nature. It implements a novel versioning algorithm called sliding snapshot, a diff-algorithm which makes use of our stable record-identifiers and optionally hashes, another diff algorithm for importing similar XML-documents as a versioned resource as well as novel XPath axis to navigate not only in space, but also in time. Recently, I've implemented a higher level, asynchronous REST-API with Kotlin (Coroutines) and Vert.x in a seperate module. The system is heavily inspired by the filesystem ZFS. My goal is to put forth the idea of a versioned, distributed storage system to easily support temporal analytical tasks, which are best applied to a series of revisions in order to analyse how the data has changes. Other tasks might simply include easy undo/redo operations. http://sirix.io December 27, 2018 at 12:42AM

Comments

Popular posts from this blog

Launch HN: Simmer (YC W19) – Reviews for Delivery Dishes https://ift.tt/2Y4sD67

Launch HN: Simmer (YC W19) – Reviews for Delivery Dishes Hi HackerNews community! We’re Vaibhav and Richard, founders of Simmer ( https://usesimmer.com ). Simmer aggregates dishes from DoorDash, Caviar, GrubHub, and basically every other delivery platform out there, and tells users the best dishes across the board. We do this by providing dish-level reviews. Users find highly reviewed dishes on Simmer, choose the delivery platform of their liking, and we deep link them into their chosen delivery app. We essentially lead gen to delivery. We started working on Simmer because we loved trying new restaurants, but never knew what to order. Especially, when there’s a 5 page menu. We always asked ourselves, “Why aren’t there ratings for individual dishes?” We launched our app with this restaurant-centric use case (reviews for every dish at every restaurant), but when we rolled out delivery integrations, we realized that users resonated most with the delivery angle. They found it particularly ...