Software · head to head
Mode vs Exa
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; Exa pricing is metered per 1,000 requests and stacks by feature: $7 per 1,000 basic searches, $12 to $15 per 1,000 for deep search variants, and separate per-ACU and per-search charges for the Agent product, as of August 2026.
Where they differ
Only the attributes on which Mode and Exa actually diverge.
Identical on both: platforms (Web), user rating (Not yet rated), category (Unknown).
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 Exa
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 Exa
- Data explorationnot Exa
- Ad-hoc reportingnot Exa
- Collaborative analysisnot Exa
- Embedded analyticsnot Exa
Exa
No use cases recorded yet. See the Exa 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
Exa
- Pricing is metered per 1,000 requests and stacks by feature: $7 per 1,000 basic searches, $12 to $15 per 1,000 for deep search variants, and separate per-ACU and per-search charges for the Agent product, 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
Exa
On requestNo published plan breakdown. See the Exa 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 Exa if
Nothing in the data separates Exa from Mode on the points above - pick on price and on how each one feels to use.
Questions people ask
- Is Mode or Exa better?
- Neither clearly leads. Mode starts at Free and Exa at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Mode or Exa?
- Mode has a free tier; the other does not. Paid plans start at Free for Mode and On request for Exa.
- Does Mode or Exa 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. Exa 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 Exa is typically brought in for.
- What can Mode do that Exa 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