I've been using Freeplay for about six months now, primarily to manage our team's dbt project and the related Looker explores. While the platform is generally competent at lineage visualization and basic documentation, I must voice a significant frustration that has been mounting: the much-touted "collaboration" layer feels almost entirely superfluous for anyone with an engineering or analytics engineering background. The features seem designed for a stakeholder persona that, in my experience, either doesn't exist or interacts with data in a fundamentally different way.
My core issue is that the collaboration tools—primarily the commenting system, the @mention functionality, and the shared canvas views—simply duplicate and, frankly, degrade workflows that are already perfectly handled by our existing toolchain. Consider a typical data quality incident:
**Current Engineer Workflow:**
1. A stakeholder reports a metric discrepancy via Slack.
2. I write and run a diagnostic SQL query in my IDE.
3. I trace the lineage in dbt or directly in the warehouse to find the root cause (e.g., a model change, a source data anomaly).
4. I fix the code in dbt, open a Pull Request in GitHub, and tag the relevant data producer.
5. The conversation, code review, and resolution all happen within GitHub, which is our system of record.
**Proposed Freeplay "Collaborative" Workflow:**
1. A stakeholder (somehow) knows to open Freeplay instead of Slack, finds the field, and leaves a comment.
2. I receive a notification (outside my normal flow), open Freeplay, and see the comment.
3. I then... leave a comment back? Or I have to navigate to my IDE anyway to actually investigate.
4. The "resolution" is a text reply in Freeplay, while the actual fix lives in a separate, unlinked GitHub PR. This creates two sources of truth.
The friction is immense. The platform asks me to bifurcate my technical work (code, SQL, pipeline logic) and my collaborative communication about that work. For engineers, these are inseparable. A comment on a line of SQL *is* the collaboration, and it needs to live with the code.
Furthermore, the feature set feels like it's solving for a "data consumer" who interactively explores live diagrams. In reality, our business users consume data through dashboards or via requests to our team. They are not logging into Freeplay to browse entity-relationship diagrams. The few times I've tried to use it for a meeting, the canvas was too noisy for a high-level explanation and not detailed enough for a technical deep-dive.
I'm left with a tool that is excellent for *individual* discovery and lineage tracing, but whose collaborative layer adds little value. It would be far more powerful if Freeplay doubled down on the engineering integration. For example:
* **Bi-directional sync with GitHub/GitLab issues.** Let a comment on a column auto-create a tracked issue in my repo.
* **Embeddable, version-aware lineage snippets** I can paste into a PR description.
* **Data quality alert integration,** where a failed test creates a collaborative thread tied directly to the failing model.
As it stands, I find myself using the platform as a sophisticated personal documentation tool, while all real collaboration remains firmly in GitHub, Slack, and Looker comments. I'm curious if other engineers have had a different experience or have found a workflow that makes these features feel essential rather than ornamental.
- dan
Garbage in, garbage out.
Interesting take. My team's experience has been a bit different, specifically when we bring in non-technical stakeholders during discovery phases.
The commenting and canvas views become a shared space for mapping out the business logic of a new model. We can tag a product manager right on a lineage node to ask, "Is this the correct transaction event?" It captures the decision in context, rather than losing it in a Slack thread.
Maybe the friction is when you're trying to bolt it onto an existing, purely technical workflow. It feels like an extra step. But when you use it to bridge the gap to business teams from the start, it actually prevents those "metric discrepancy" fire drills later. The context lives with the asset.
Let the machines do the grunt work
Spot on about the workflow duplication. We tried similar features in DataHub and it was the same story - another inbox to check, another place for context to get orphaned.
The killer for us was during a PagerDuty alert at 2AM. My brain is in CLI/terminal mode, tracing lineage with SQL or `dbt ls -r`, not logging into some web UI to click around a canvas. That stuff is for post-mortems, not firefighting.
These tools assume everyone's working 9-5 on greenfield projects. Try using them when your pipeline is broken and Slack is blowing up.
NightOps
You're right, but I think you're missing the vendor's real goal.
That "superfluous" layer isn't for your workflow. It's a sales feature aimed at executives who sign the checks. The stakeholder persona is the budget holder who wants a pretty, unified interface to point to. It creates the illusion of cross-functional alignment, which justifies a higher seat price and locks the platform in deeper.
Your efficient engineering workflow doesn't expand contract value. A canvas that a PM can log into does.
Trust but verify.