We just completed a migration from Qlik Sense to ThoughtSpot for our primary internal analytics. The driver was twofold: end-user frustration with dashboard load times on complex datasets, and our finance team's inability to easily explore data without writing new Qlik apps.
The performance difference is stark. Our main sales dataset (~1.2B rows) in Qlik would take 45-60 seconds to load on opening, with subsequent filters causing noticeable lag. In ThoughtSpot, the initial search loads in under 10 seconds. The shift from a pre-built dashboard model to a search-driven interface was a cultural change, but adoption has been surprisingly high among non-technical teams.
Key technical observations:
* **Underlying architecture:** We were on Qlik's in-memory engine. ThoughtSpot's in-memory columnar store seems more efficient for our type of queries, which often involve high-cardinality dimensions.
* **Modeling:** Qlik's associative model was powerful but confusing for users. ThoughtSpot's simpler "table-and-join" model was easier for our data team to manage, though it lacks some of Qlik's script-level flexibility.
* **Cost:** This is the FinOps angle. Our Qlik license cost was significant and tied to core count. ThoughtSpot's consumption-based model (based on data volume and active users) aligns better with our variable usage, but we had to implement monitoring to avoid runaway "search" costs.
Biggest win: The finance ops team now builds their own reports. In Qlik, they'd file a ticket. Now they search. Biggest challenge: Recreating some of our complex Qlik set analysis for YTD comparisons required rethinking the data model.
Has anyone else made a similar move? I'm particularly interested in how you handled:
* Re-education on moving from dashboards to search
* Long-term cost comparisons after 12+ months
* Any specific data modeling pitfalls you hit
Interesting read. I've been evaluating ThoughtSpot for a while, and your 1.2B row performance numbers are exactly what I've been hearing from other teams. That 10-second search vs 45-60 second dashboard load is a no-brainer for user experience.
One thing I'm curious about: you mentioned Qlik's script-level flexibility being lost. Have you run into any gnarly data transformations that you used to handle in the Qlik load script but now have to push upstream to ETL? That's been my biggest hesitation - Qlik's associativity might be confusing for end users, but for power users who knew how to leverage set analysis and the script engine, it was a Swiss army knife. ThoughtSpot's modeling seems to assume you've already got a clean star schema ready to go.
Also, on the adoption front - any friction with the "search" paradigm for users who were used to pre-built dashboards with KPIs already laid out? I've seen some teams struggle because they expect the dashboard to tell them what's important, not a blank search bar.
Spreadsheets > marketing slides.
That's a really sharp question about data transformations. You're right about the clean star schema assumption. We had to rework a few key pieces.
The biggest shift was with time-based calculations that used to live in the Qlik script, like rolling 12-month averages and period-over-period comparisons for custom fiscal calendars. In ThoughtSpot, we had to model these as explicit columns in our data warehouse views or use their ANSWER_TIME function if the logic was simple enough. It felt restrictive at first, but honestly, it forced better discipline. Our data team now owns those transforms in dbt, which is probably where they belonged anyway. Has that been your experience when looking at their modeling layer?
On adoption, the blank search bar was a hurdle. We countered it by building "starter" saved searches - basically pre-written questions like "sales by region this quarter" that users could click and then modify. It gave them a template instead of a blank page. The finance team actually took to it faster than our sales ops people, go figure.