Every company has the idea of the “nightly report.” A business analyst comes into the office, sits down in front their inbox, and looks at yesterday’s data. Did sales go up? Did the marketing campaigns bring in the expected number of customers? Was there an increase in helpdesk tickets? The statistics that these reports deliver

Searching through all of the videos on the Internet is not a simple problem. In order to search through all the videos, you need to build a search index. In order to build a search index, you need to build a web crawler. Video files are large. To store all of the actual video files

Over the last decade, cloud computing made it easier to programmatically define what infrastructure we have running, and perform operations across that infrastructure. This is called “infrastructure as code.” Whether you want to backup a database, deploy a new version of a service, or introduce a new tier of load balancers, the changes that we

Twenty years ago, all of the data in an organization could fit inside of relational databases. Imagine a company like Proctor and Gamble. P&G is a consumer packaged goods company with hundreds of business sectors–shaving products, toothpaste, shampoo, laundry detergent. Twenty years ago, if the chief financial officer of P&G wanted to answer a question

Relational databases have been popular since the 1970s, but in the last 20 years the amount of data that applications need to collect and store has skyrocketed. The raw cost to store that data has decreased. There is a common phrase in software companies: “it costs you less to save the data than to throw

Ten years ago, a biology researcher was limited by the software tools available. Most of the electronic record keeping was done using Excel and other general purpose tools. Benchling is a suite of software tools that were designed to simplify the lives of life science researchers. Benchling helps with sample tracking, experiment design, and workflow

When a user takes a ride on Uber, the app on the user’s phone is communicating with Uber’s backend infrastructure, which is writing to a database that maintains the state of that user’s activity. This database is known as a transactional database or “OLTP” (online transaction processing). Every active user and driver and UberEATS restaurant

Cloud computing lowered the cost and improved accessibility to tools for storing large volumes of data. In the early 2000s, Hadoop caused a revolution in large scale batch processing. Since then, companies have been building ways to store and access their data faster and more efficiently. At the same time, the sheer volume of data

Phones are constantly tracking the location of a user in space. Devices like cars, smart watches, and drones are also picking up high volumes of location data. This location data is also called “geospatial data.” The amount of geospatial data is rapidly increasing, and there is a growing demand for software to perform operations over

There are hundreds of different databases. There are tens of continuous delivery products. There is an ocean of cloud providers and CRM systems and monitoring platforms and sales prospecting tools. The range of available software products is so diverse that it can be overwhelming to figure out which products to buy. Siftery is a company