Analytical databases are often centered around metrics and measures, with dimensions organized into a rigid multi-dimensional cube structure. But this model struggles when the dimensions themselves need to change or evolve over time.

Welcome back to our podcast. In the previous episode of the Clarisights Sessions podcast we kicked off the Mozek Dev Diaries. In the first episode we looked the concept of orchestrators and why they are so important to the Clarisights tech stack. In this second epiosde, we really get stuck

Say 👋🏽 to Clarisights Sessions, our new, official podcast. Entirely produced in-house, Sessions will tell stories about the things that we are passionate about. Expect to hear about SaaS, engineering, people, talent, and customers. We kick off the new podcast with a mini-series called How To Build A Brain: The Mozek

Clarisights empowers performance marketing teams at some of the world’s most innovative companies to take meaningful decisions. We do this by democratising data through our revolutionary no-code BI reporting platform. Sitting at the heart of the Clarisights platform is MorselDB. MorselDB is the proprietary database technology that enables our

At Clarisights, we run all of our stateless workloads on Kubernetes and utilize Graphite and InfluxDB for monitoring. As every other software company, we also see uneven traffic spikes from the user activities and batch jobs. To handle this, we used to provision for peak capacity but that meant most

The post will show how we scaled a lot of our time-consuming background jobs by 100X and more. Obviously, 100X is relative to where we were before. Our previous post covered some of the optimizations we did earlier and how the setup looks like. For sake of brevity, we won’

At Clarisights, we are building an automated BI platform for enterprise performance marketing teams. Our goal is to help non-SQL literate business users to ask questions about their data at the deepest granularity without worrying about pipelines, data de-normalization or writing complex queries. We enable customers to create “custom metrics”

Sidekiq is famous (in the Ruby world) as an easy and simple background job processing solution. Sidekiq covers almost all the use cases that you expect from a background job processing solution but sometimes you need something that is not supported out of the box. That’s when Sidekiq middleware

Like most fast growing startups building the next generation technical platform, we, at Clarisights engineering, are always trying to balance the speed with which we push out new features and finding ways for the performance of the system to keep pace with this speed. There are standard established techniques for

The Problem We have a Rails backend and use Postgresql as our OLTP DB. About a month back, we moved to Rails 5.2. Ever since we noticed that our queries to PG in our background jobs will randomly fail. Errors would look like PG::ConnectionBad: PQconsumeInput(). These errors, in

In today’s post, I will cover what all we did to optimize to our backend system which is a Ruby on Rails application. Background AdWyze (now Clarisights) uses Ruby on Rails and as a data integration platform and we talk to multiple external sources. In fact, we keep fetching