Okay, I have to get this off my chest. I've been wrestling with Sumo Logic's query language for a good six months now, trying to integrate it into our product analytics workflows, and I'm hitting a wall. It feels like I'm writing a novel every time I want to do something moderately complex. Compared to some other tools I've used (looking at you, Mixpanel and Amplitude for behavioral stuff, or even Splunk's SPL for logs), the syntax just feels... heavy.
I came in super excited about the platform's power for correlating user behavior with system events. The concept is a product-led growth dream! But the execution in the query pane leaves me spending more time on syntax than on insight.
Here’s a simple example: I wanted to see feature adoption for a new checkout button, segmented by user cohort (sign-up week), and filter out internal IPs. In other tools, this might be a few lines. In Sumo, I feel like I'm writing a dissertation. The sheer number of `parse`, `timeslice`, and `count by` clauses just to get a clean time-series for cohorts makes my head spin.
My specific pain points:
* **The `where` clause nesting** for multiple conditions gets visually messy so fast. It's hard to scan.
* **Aliasing and re-aliasing** fields for multi-step aggregations feels redundant. I have to constantly remind the query what I just told it.
* **Common cohort analyses**—like comparing the week 1 retention of a January cohort vs a February cohort—require a staggering amount of subqueries and joins. It's doable, but the cognitive load is high.
* **The verbosity obscures the business logic.** When I finally get a query working, it's so long that my product manager peers glaze over. The story gets lost in the syntax.
Am I missing something? Is there a secret handshake or a more efficient pattern I haven't learned? I've gone through the training docs, but they seem to celebrate the complexity as "power."
I love the data that's in there, and the dashboards are solid once built. But the journey to get there is so friction-heavy that it discourages experimentation. For a product analytics person who lives in the "what if we segment by this?" world, that's a real problem.
Has anyone else felt this way? Have you developed any shortcuts, template strategies, or mental models to make it feel less like you're writing legal code and more like you're exploring data?
🔥
Try everything, keep what works.
I hear you on the verbosity. That transition from something like Mixpanel's interface to Sumo's query language can feel like switching from a sports car to a manual transmission truck. You're right, the nesting gets visually complex quickly.
One thing that helped me was leaning into named queries and the 'save as' function for those common patterns, like filtering internal IPs. It doesn't make the underlying syntax shorter, but it reduces the novel-writing for each new dashboard.
Could you share the rough structure of that checkout button query? Sometimes there are ways to refactor the parse statements that cut down the clutter a bit.
Keep it constructive.