RocksDB is a storage engine based on the log-structured merge tree data structure. RocksDB was developed at Facebook to provide a tool for embedded databases. The code for RocksDB is a fork of LevelDB, an embedded database built by Google for the Chrome browser. Every database has a storage engine. The storage engine is the

When a user interacts with an application to order a ride with a ridesharing app, the data for that user interaction is written to a “transactional” database. A transactional database is a database where specific rows need to be written to and read from quickly and consistently. Speed and consistency are important for applications like

Netflix has thousands of service instances communicating with each other. When a Netflix client on a smartphone makes a request for a movie, that request hits Netflix’s backend, where the request is fulfilled by a chain of requests through different services. Services and clients communicate using several different interaction patterns. A service might send a

If a business has been operating successfully for a few years, that business has accumulated a high volume of data. That data exists in spreadsheets, CSV files, log files, and balance sheets. Data might be spread across local files on a user’s laptop, databases in the cloud, or storage systems in an on-premise data center.

Netflix has petabytes of data and thousands of workloads running across that data every day. These workloads generate movie recommendations for users, create dashboards for data analysts to study, and reshape data in ETL jobs, to make it more accessible across the organization. Over the last ten years, data engineering has become a key component

At Facebook, Venkat Venkataramani saw how large volumes of data were changing software infrastructure. Applications such as logging servers and advertising were creating fast moving, semi-structured data. The user base was growing, the traffic was growing, and the volume of data was growing. And the popular methods for managing this data were insufficient for the

Demand for live streaming video over the internet is increasing. After the emergence of early live streaming platforms, like Twitch and Facebook Live, more forms of video have become accessible over live streams, such as sports. Live streaming is a harder engineering problem than delivering a static video file because the information distributed on a

Mapillary is a company that processes high volumes of images to develop a labeled 3-D model of the physical world. Mapillary’s APIs allow developers to build applications that are aware of stop signs, buildings, streets, trees, and other physical objects in real-world space. The potential use cases for Mapillary are numerous, ranging from self-driving cars

DevSecOps emphasizes moving security out of a siloed audit process and distributing security practices throughout the software supply chain. In the past, software development usually followed a waterfall development process. Each step in building software was serialized, one after another. First, software was planned. Then it was built. Then it was tested. Finally, the software

Search is part of almost every application. Users search for movies to watch. Engineers search through terabytes of log messages to find exceptions. Drivers search through maps to find a destination. Search remains an unsolved problem, with lots of room for optimization. Many search applications have been built Elasticsearch, an open source distributed search engine.