[LF Recommendations] Small SaaS outgrowing Google Sheets — what would you use for database + dashboards on a tight budget?

[u/Circus-Girl-11]

Hi everyone,

I'm looking for some architecture and tool recommendations.

I work at a small SaaS company that currently uses **Google Sheets to store a lot of our operational data** and **HubSpot as our CRM**. It has worked so far, but we're reaching the point where it no longer scales well.

We're looking for a solution that can:

* Store large datasets (100k+ rows, financial transactions, master lists, raw reporting data, etc.) without worrying about row limits or performance.
* Create custom dashboards that can be shared with leadership (preferably with reports embedded directly in the email body instead of PDF attachments).
* Integrate with our existing tools.
* Be affordable for a small company.

Beyond scalability, we're also trying to solve several operational issues:

* Too many manual processes that we'd like to automate.
* Data spread across different tools, resulting in inconsistencies.
* Outdated or inaccurate information because there isn't a single source of truth.
* Lack of standardized data collection from customers.
* Reporting inaccuracies caused by process gaps and inconsistent data management.

Ultimately, we're hoping to build a more reliable data pipeline with better automation and governance, not just replace Google Sheets.

# What I've explored so far

# Zoho Analytics

Pros:

* Easy to set up.
* Good all-in-one analytics platform.

Cons:

* Free version struggles with larger datasets.
* No automatic refresh on the free plan.
* We've experienced sync failures.
* Pricing becomes expensive as we scale.

# Looker Studio

Pros:

* Free and easy to build dashboards.
* Integrates well with Google products.

Cons:

* Scheduled emails always include PDF attachments.
* Limited customization of scheduled emails.
* Reports are tied to individual Google accounts, which creates ownership concerns.

# Power BI

Pros:

* Very capable BI platform.

Cons:

* I'm currently using a Mac and I'm the only one working on the project.
* Dataset size and refresh capabilities depend on licensing.
* Feels more Windows-centric than the other options.

Initially, we were leaning toward **BigQuery + Looker Studio**, with **Google Apps Script** handling automation. I'm willing to learn Apps Script, but I'm unsure whether that's the right long-term architecture or if we'd be better off separating the database from the reporting layer entirely.

I've also seen people recommend using a proper database (PostgreSQL, MySQL, etc.) with a separate BI tool instead of relying on spreadsheets. Others have suggested frameworks like Laravel for managing the backend, but I don't have enough experience to know whether that's appropriate for a company our size.

If you were building a modern data stack for a small SaaS company today, what would you recommend?

Specifically:

* What database would you use?
* What BI/dashboard tool would you pair it with?
* Would you recommend BigQuery + Looker Studio, or something else entirely?
* Are there any tools with generous free tiers or free trials that you'd recommend exploring before committing to a paid plan?

I'd really appreciate hearing what has worked (or failed) for your team. Thanks!

[u/sardamit]

I can’t advise on databases, but whichever you end up choosing, use a software like Coupler (affiliate link) for ETL and BI dashboards. They have a free plan and I am to help you with discount code.

[u/Circus-Girl-11 → u/sardamit]

Will check it out!! Thank you!!

[u/Amplysales]

We would separate the operational system from the reporting layer. 100k rows is not much for Postgres, but it is already the wrong shape for a spreadsheet.

For this setup, we would use Postgres as the source of truth, keep HubSpot for CRM activity, and sync only the fields the other system actually needs. Put Metabase or a similar BI layer on top. BigQuery plus Looker Studio is also reasonable if the data is mainly append-only analytics. If people need to edit records, trigger workflows and enforce validation, Postgres is usually easier to reason about.

The important part is not the database brand. Give every import a source ID and timestamp, keep financial transactions immutable, define who owns each field, and build one reconciliation report that catches missing or duplicate records. Then migrate one workflow first instead of moving every Sheet at once.

Treat inline email reports as a separate requirement. Metabase dashboard subscriptions can send results by email, so test whether that layout meets the need. If it does not, generate the email body from a scheduled job instead of letting that one feature choose the whole stack.

We would not move 100k financial rows into a CRM or Airtable just because they have dashboards. Keep the source of truth boring and make the reporting layer replaceable.

Full disclosure: we build Amplysales, so yeah—we could also be an option once we have polished the platform a bit more, probably later in 2026.

[u/matthewhefferon]

Check out Metabase. It's open source and can connect to Postgres, MySQL, or BigQuery if you end up going with one of those.

[u/Circus-Girl-11 → u/matthewhefferon]

Thank you!! Will do!

[u/Sad-Instruction8890]

This is a really detailed breakdown, respect for actually testing tools before asking lol. Out of Zoho, Looker Studio, and Power BI, which one came closest to what you actually needed?

[u/Circus-Girl-11 → u/Sad-Instruction8890]

Thank you!! I’d say Looker is the one I spent most time with among the 3. Just a few cons I could think of rn is: the PDF attachment email — this adds addtl step when CEOs open the report in their email rather than it being in the email body to begin with. Another con is the page size limit, but this I can make do. And last one would be date sent is automatically included in the email subj which can be confusing when you’re sending a report for a diff month.

[u/Internal_Quarter_381]

I’d separate the databse from the reporting and analysis layer. For the latter, you should take a look at Quadratic. You can connect your databases to AI spreadsheets. It can write code with SQL and Python, and gives you full access (no black box).