A data pipeline is a series of steps that takes large data sets and creates usable results from them. At the beginning of a data pipeline, a data set might be pulled from a database, a distributed file system, or a Kafka topic. Throughout a data pipeline, different data sets are joined, filtered, and statistically

A data warehouse provides low latency access to large volumes of data.  A data warehouse is a crucial piece of infrastructure for a large company, because it can be used to answer complex questions involving a large number of data points. But a data warehouse usually cannot hold all of a company’s data at any

Distributed stream processing systems are used to read large volumes of data and perform operations across those data streams.  These stream processing systems often build off of the MapReduce algorithm for collecting and aggregating large volumes of data, but instead of processing a calculation over a single large batch of data, they process data on

Large companies generate large volumes of data. This data gets dumped into a data lake for long-term storage, then pulled into memory for processing and analysis. Once it is in memory, it is often read into a dashboard, which presents a human with a visualization of the data.  The end-user who is consuming this data

Data infrastructure has been transformed over the last fifteen years.  The open source Hadoop project led to the creation of multiple companies based around commercializing the MapReduce algorithm and Hadoop distributed file system. Cheap cloud storage popularized the usage of data lakes. Cheap cloud servers led to wide experimentation for data tools. Apache Spark emerged

A data platform contains all of the data that a company has accumulated over the years. Across a data platform, there is a multitude of data sources: databases, a data lake, data warehouses, a distributed queue like Kafka, and external data sources like Salesforce and Zendesk. A user of the data platform often has a

Nubank is a popular bank that is based in Brazil. Nubank has more than 20 million customers, and has accumulated a high volume of data over the six years since it was started. Mobile computing and cloud computing have given rise to “challenger banks” that operate more like software companies. When a software company reaches

Stock trading takes place across a variety of software platforms. Etrade and Schwab have allowed individual traders to buy securities for decades. Robinhood built a business around a similar model, but also removed the commission. Wealthfront and Betterment provide “roboadvisor” services that abstract away the underlying securities and focus on managing a risk profile. Each

GraphQL has become a core piece of infrastructure for many software applications. GraphQL is used to make requests that are structured as GraphQL queries and responded to through a GraphQL server. The GraphQL server processes the query and fetches the response from the necessary databases, APIs, and backend services. Around 2016, when GraphQL was becoming

Every large company generates large amounts of data. Data engineering is the process of storing, transforming, and leveraging that data. Data infrastructure companies provide tools and platforms for performing data engineering. The last fifteen years has seen a rise in modern data management companies built in a time of decreasing storage costs, an increased volume