Open-Source Looker Studio (Data Studio) Alternatives in 2026

Looker Studio is a good free dashboarding tool, and it connects easily to BigQuery, Google Sheets and Google Ads. But it is proprietary, hosted only by Google, and your reports live in Google's cloud. I am Manoj, a consultant at MithTech, a team of Frappe specialists in Bengaluru. I set up self-hosted dashboards for clients running ERPNext, multi-location operations and large financial datasets, and I have run both Superset and Metabase in production.

If your data already lives in Google's ecosystem, Data Studio's free tier is hard to beat. The reason to move to open source is ownership and control, not a lower price.

Which open-source tools replace Looker Studio?

Apache Superset and Metabase. Superset leads on depth: a SQL workbench and a large chart library, including geospatial charts, for data-fluent teams. Metabase leads on ease: a visual question builder lets non-technical staff answer questions without SQL. Both self-host, so reports never leave systems you control.

They come at the Looker Studio job from opposite ends. Superset starts from the analyst and adds governance and scale. Metabase starts from the business user and adds power as you grow. Neither hosts your dashboards in a vendor's cloud; you run them on your own server, in a region you choose. For the wider pattern of replacing rented SaaS with owned tools, see open-source SaaS alternatives.

Skimmable summary: Superset is deepest for data teams; Metabase is easiest for business users; both self-host.

Why look for an open-source Looker Studio alternative?

Data ownership and lock-in. Open-source dashboards run on infrastructure you control, so your reports, queries and connection credentials do not live in a vendor's cloud. Data Studio is free and polished, but Google-hosted and Google-tied: once most of your data sits outside Google's ecosystem, its convenience shrinks and the lock-in remains.

Google renamed Looker Studio back to Data Studio in April 2026, positioning it for personal and ad-hoc reporting across BigQuery, Sheets and Ads, with Looker kept as the governed enterprise product. That is its strength and its limit: it shines when your data is already in Google's cloud, and leans on a connector marketplace for everything else, much of it third-party and paid. With Superset or Metabase, you connect directly to your own databases, keep the data on your servers, and can read or change the source code. Nobody can change the product's name, pricing or connector policy under you.

Skimmable summary: move for data ownership and freedom from Google lock-in; Data Studio stays strong inside Google's ecosystem.

Apache Superset vs Metabase: which fits you?

Team skill decides it. Superset assumes SQL fluency and rewards it with a stronger query workbench and more chart types. Metabase lets a sales or finance manager build a chart by clicking through a question, with SQL underneath for analysts.

The pick is about who will use and run the tool. For heavier BI work, and the step-by-step ERPNext connection, see the open-source Power BI alternative guide.

Skimmable summary: Superset for SQL-fluent data teams; Metabase for mixed business teams who want a no-code builder with SQL underneath.

How do Superset and Metabase compare to Looker Studio?

For the core job (connect a data source, explore, build charts, assemble dashboards, share them, schedule reports) Superset and Metabase cover what most businesses use Looker Studio for. The gaps are at the edges: Data Studio's zero-setup convenience and its native links into Google Ads, Analytics, Sheets and BigQuery.

If your reporting revolves around Google Ads, GA4 and Sheets, Data Studio's native connectors are hard to match with no setup. For dashboards on your own operational data (sales, inventory, finance in a database you run), the open-source pair is enough and keeps the data yours.

Skimmable summary: for core dashboarding the open-source pair matches what most teams use; Data Studio still leads on zero setup and native Google marketing data.

How do you get Google Ads and GA4 data into Superset or Metabase?

Through a database, because neither tool has Google marketing connectors. The usual route is BigQuery, which both can query directly.

This keeps BigQuery in the loop, so it is not a full exit from Google; it does move the dashboards and the joins with your own data into tools you run. If Google marketing data is all you report on, staying on Data Studio is simpler.

Skimmable summary: Ads via the BigQuery Data Transfer Service, GA4 via its BigQuery export, then Superset or Metabase on BigQuery.

What are the gaps in open-source dashboards?

Operating effort is the main cost. Self-hosting means you handle installation, upgrades, backups, security patches and scaling, which Google absorbs with Data Studio. Superset in particular needs real engineering capacity to run well at scale; Metabase is lighter but still needs an owner.

There are feature gaps too. Superset connects to SQL databases through SQLAlchemy, so it does not pull arbitrary marketing APIs the way Data Studio's connector marketplace does: you point it at a database, not at a hundred SaaS connectors. Metabase's AGPL edition is generous, but some governance and embedding features sit in its paid editions. And neither offers click-to-connect Google Ads and Analytics reporting.

Skimmable summary: you run and secure the tool; Superset needs a database, not connectors; some Metabase features are paid; no native Google marketing reporting.

How do you connect open-source dashboards to ERPNext?

Directly to the database. ERPNext runs on MariaDB, and both Superset and Metabase connect to it, ideally through a read replica with a read-only user so dashboard queries never slow live transactions. Then you model the tables you report on most into Superset datasets or Metabase questions, build dashboards per team and schedule them. The Power BI alternative guide walks through those steps; the ERPNext platform page covers the system underneath.

Skimmable summary: connect to ERPNext's MariaDB through a read-only user on a replica, then model, build and schedule.

Who should stay on Looker Studio?

Teams whose reporting is Google-centric. Marketing and analytics teams with data in Google Ads, Analytics, BigQuery and Sheets get native, zero-setup connectors that open-source tools cannot match without the BigQuery route above. Teams with no appetite to self-host anything, who want free hosted dashboards with nothing to maintain, are also well served by staying.

The moment you want dashboards on your own operational database, care about data residency, or already run open-source systems like ERPNext, Superset and Metabase become the better long-run choice: you own the tool, the data and where both live.

Skimmable summary: stay on Data Studio if reporting centres on Google Ads, Analytics and Sheets, or you cannot self-host; move when you want dashboards on your own database.

Frequently asked questions