Business Intelligence · head to head
Mode vs Glean
The short version
- Only Mode has a free tier, so it costs nothing to try first.
- Each has a real cost: Mode free tier limited to 4GB RAM and 1 CPU for SQL notebooks, insufficient for large datasets; Glean glean publishes no self-serve pricing tiers at all; both the homepage and dedicated pricing page route every visitor to a demo request with no plan names or figures shown, as of August 2026.
Where they differ
Only the attributes on which Mode and Glean actually diverge.
Identical on both: platforms (Web), user rating (Not yet rated), category (Business Intelligence).
What each one covers
Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.
Only in Mode
- SQL Editor
- Python/R Notebooks
- Interactive Reports
- Version Control
- Scheduling
- Snowflake
- Redshift
- BigQuery
Only in Glean
Nothing recorded that Mode does not also cover.
What people use each for
The jobs each tool is most often brought in to do.
Mode
- Self-service analyticsnot Glean
- Data explorationnot Glean
- Ad-hoc reportingnot Glean
- Collaborative analysisnot Glean
- Embedded analyticsnot Glean
Glean
No use cases recorded yet. See the Glean review.
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Mode
- Free tier limited to 4GB RAM and 1 CPU for SQL notebooks, insufficient for large datasets
- Requires SQL knowledge for most analysis tasks, creating dependency on technical resources
- Paid plan pricing not publicly listed; requires sales consultation
- Recently acquired by ThoughtSpot in 2026, creating product direction uncertainty
- Limited customization options for visual aspects and embedded analytics
Glean
- Glean publishes no self-serve pricing tiers at all; both the homepage and dedicated pricing page route every visitor to a demo request with no plan names or figures shown, as of August 2026.
Pricing, plan by plan
Mode
Free- FreeFree
- SQL Editor
- Python/R Notebooks
- Basic Charts
- Business$65/month
- Advanced Visualizations
- Collaboration
- Integrations
Glean
On requestNo published plan breakdown. See the Glean review.
Which should you pick?
Choose Mode if
- You need sql editor.
- You want to start without paying.
- You also want python/r notebooks.
Choose Glean if
Nothing in the data separates Glean from Mode on the points above - pick on price and on how each one feels to use.
Questions people ask
- Is Mode or Glean better?
- Neither clearly leads. Mode starts at Free and Glean at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Mode or Glean?
- Mode has a free tier; the other does not. Paid plans start at Free for Mode and On request for Glean.
- Does Mode or Glean run on more platforms?
- Both run on Web, so platform support will not decide this one for you.
- Can I use Mode for free?
- Yes. Mode has a free tier, so you can try it without paying. Glean starts at On request.
- What is Mode best used for?
- Mode is most often used for self-service analytics, data exploration, ad-hoc reporting, collaborative analysis. Of those, self-service analytics and data exploration are not what Glean is typically brought in for.
- What can Mode do that Glean cannot?
- Mode covers SQL Editor, Python/R Notebooks, Interactive Reports, Version Control.
Answered from the vendors’ own pages
Mode: What languages does Mode support for analysis?
Mode notebooks support SQL, Python (3.11 with pandas, NumPy, scikit-learn, matplotlib), and R (4.2.0 with ggplot2, dplyr, tidyr). Both Python and R allow additional library installation at runtime.
SourceMode: Can I integrate Mode notebook results into reports?
Yes. Mode allows adding notebook cell results directly to reports, with synchronized scheduling so reports re-run to keep data current.
SourceMode: Does Mode support collaborative analysis?
Yes. Mode notebooks provide moveable code blocks and markdown cells enabling exploratory analysis and team collaboration on data queries and visualizations.
Source