Presto is a distributed query engine that allows querying different data sources such as Kafka, MySQL, MongoDB, Oracle, Cassandra, Hive, etc. using SQL. It has the ability to analyze big data and query multiple data sources together.
In this article, we will discuss how Presto can be used to query Kafka topics. Below is the step-by-step process to set up Presto and Kafka, and connect them together. Here, I have considered MacOS, but similar setups can be done on any other system.
This guide was developed using a laptop running Windows OS and docker on it.
This guide was developed using a laptop running Windows OS and docker on it.
The author, Jordan Hoggart, was not compensated by Ahana for this review.
At the base of Carbon’s real-time, first-party data platform is our analytics component, which combines a range of behavioral, contextual, and revenue data, which is then displayed within a dashboard in a series of charts, graphs, and breakdowns to give a visual representation of the most important actionable data. Whilst we pre-calculate as much of the information as possible, there are different filters that allow users to drill deeper into the data, which makes querying critical.
The need for data engineers and analysts to run interactive, ad hoc analytics on large amounts of data continues to grow explosively. Data platform teams are increasingly using the federated SQL query engine PrestoDB to run such analytics for a variety of use cases across a wide range of data lakes and databases in-place, without the need to move data. PrestoDB is hosted by the Linux Foundation’s Presto Foundation and is the same project running at massive scale at Facebook, Uber and Twitter.
Let’s look at some important characteristics of Presto that account for its growing adoption.
