This blog post was originally featured on the Qlik Branch Blog in April 2020. It has been updated to reflect recent changes.
When my business partner and I conceived of the idea for our data analytics tool Knarr, we knew that we wanted to build an experience for ad-hoc, collaborative data analysis. An experience where teams could quickly navigate through their data, combine their insights, and make decisions based on shared understanding. With Knarr, analysts and advanced business users could respond to the daily demands of life with faster and more informed decisions than ever before.
To fulfill our vision with Knarr, we needed to find the right analytics engine to power our experience. There were hundreds of options in the market and the open-source community to consider. In reviewing our options, we knew we needed a solution that could handle high data volumes, sophisticated queries, and high concurrency. These criteria led us to Qlik Core.
There are several aspects of Qlik Core that made it a great fit for us:
- Speed: the Engine can process complex queries over high data volumes quickly
- Multiple data sources: in ad-hoc analysis, data wrangling is key. Qlik provides built-in support for linking disparate data
- Shared state: Qlik’s concept of a session with data in-memory provides unique possibilities for how to share analytics across users
- Advanced APIs: Qlik Core provides innovative tools for data manipulation like the Tree API — key to producing advanced charting at scale
Qlik Core also fits our infrastructure needs well. It is offered as a Dockerized service, which gives us control over how we architect and scale our deployments. This is key for us as a new company with a cloud-based offering.
Beyond the technical aspects of Qlik Core, working with the R&D team at Qlik has been a positive and smooth experience for our small team. The Qlik team is receptive to feedback and has been excellent to work with, which has made the platform easy for us to use and build on. The product is constantly being advanced, allowing us to do more with our stack over time.
With Qlik Core as a rock-solid part of our infrastructure, we’ve been able to rapidly expand on our vision of providing a truly collaborative and explorative data analysis experience with Knarr. Some of our innovative features made possible with Qlik Core include:
- Multiplayer Mode: Users can enter a shared workspace and analyze datasets together in real-time or show other users how they are finding insights
- Notes: Notes allow you to document thoughts on each project and include links (Snapshots) that allow users to jump to relevant analyses
- Snapshots: These capture point-in-time views of data analysis and allow users to jump back to the exact analysis other users capture including relevant data sets and visualizations
- Sophisticated Filters: Knarr includes complex yet accessible filtering mechanisms that enable users to ask more sophisticated questions of their data
- Timeline: The Timeline is an innovative feature that saves a history of users’ actions within Knarr. There is no need to obsessively take snapshots of each point in your analysis because each change is captured along the timeline. You can use this history to jump back to any point in your work.
To see more about what we’re doing in this space, sign up for free at knarr.io.