Edgestore is the metadata store that powers many internal and external Dropbox services and products. We first talked about Edgestore in late 2013 and needless to say, much has happened since.
In this post, we give a high-level overview of the motivation behind Edgestore, its architecture, salient features and how it’s being used at Dropbox. We’ll be doing a deep-dive on various aspects of Edgestore in subsequent posts.
A Brief History
Like so many startups, Dropbox started with vanilla MySQL databases for our metadata needs. As we rapidly added both users and features,
Dropbox’s document scanner lets users capture a photo of a document with their phone and convert it into a clean, rectangular PDF. It works even if the input is rotated, slightly crumpled, or partially in shadow—but how?
In our previous blog post, we explained how we detect the boundaries of the document. In this post, we cover the next parts of the pipeline: rectifying the document (turning it from a general quadrilateral to a rectangle) and enhancing it to make it evenly illuminated with high contrast. In a traditional flatbed scanner,
A few weeks ago, Dropbox launched a set of new productivity tools including document scanning on iOS. This new feature allows users to scan documents with their smartphone camera and store those scans directly in their Dropbox. The feature automatically detects the document in the frame, extracts it from the background, fits it to a rectangular shape, removes shadows and adjusts the contrast, and finally saves it to a PDF file. For Dropbox Business users, we also run Optical Character Recognition (OCR) to recognize the text in the document for search and copy-pasting.
We are pleased to announce the open source release of Lepton, our new streaming image compression format, under the Apache license.
Lepton achieves a 22% savings reduction for existing JPEG images, by predicting coefficients in JPEG blocks and feeding those predictions as context into an arithmetic coder. Lepton preserves the original file bit-for-bit perfectly. It compresses JPEG files at a rate of 5 megabytes per second and decodes them back to the original bits at 15 megabytes per second, securely, deterministically, and in under 24 megabytes of memory.
We have used Lepton to encode 16 billion images saved to Dropbox,
There is nothing more important to Dropbox than the safety of our user data. When we set out to build Magic Pocket, our in-house multi-exabyte storage system, durability was the requirement that underscored all aspects of the design and implementation. In this post we’ll discuss the mechanisms we use to ensure that Magic Pocket constantly maintains its extremely high level of durability.
This post is the second in a multi-part series on the design and implementation of Magic Pocket. If you haven’t already read the Magic Pocket design overview go do so now;
Written by Daniel Reiter Horn and Mehant Baid, Serving Infrastructure team at Dropbox.
In HBO’s Silicon Valley, lossless video compression plays a pivotal role for Pied Piper as they struggle to stream HD content at high speed.
John P. Johnson/HBO
Inspired by Pied Piper, we created our own version of their algorithm Pied Piper at Hack Week. In fact, we’ve extended that work and have a bit-exact, lossless media compression algorithm that achieves extremely good results on a wide array of images. (Stay tuned for more on that!)