Which open-source BI tool fits your team's situation
Choose Apache Superset if your analysts work in SQL and you have platform engineering capacity to run it. Choose Metabase if business users need self-serve exploration and your budget can cover paid Pro or Enterprise plans for SSO and row-level security. Redash fits a lighter SQL dashboard tool, while Lightdash and Grafana cover dbt-centric and operational dashboards. Start by listing the identity and data-access controls your policy makes non-negotiable, because those requirements usually narrow the shortlist before dashboard features do. An SSO mandate, group-based roles or restricted datasets will decide more of the outcome than chart types will.
The license terms differ more than the feature lists suggest. Apache Superset is Apache-2.0 with no paid edition. Metabase ships its open source edition under the AGPL, code in its enterprise directory falls under the Metabase Commercial License, and its paid Pro and Enterprise plans add SSO and row and column level permissions. Redash is BSD-2-Clause, and Grafana is AGPL-3.0-only since version 8.0, with Grafana Enterprise as a separate commercial edition. Apache-2.0, BSD-2-Clause and AGPL are all OSI-approved, so none of these is proprietary, but their obligations differ. AGPL terms can apply when you modify the software and let users interact with it over a network, so have legal counsel confirm what applies to your deployment. Metabase Enterprise is priced by quote starting at $20,000 per year, according to its pricing page, so budget for the paid tier before you commit to a feature that requires it.
Confirm the identity path before you test any tool. Superset supports OAuth2 providers, custom OAuth2 servers and LDAP, maps groups to roles with AUTH_ROLES_MAPPING, and requires you to set SECRET_KEY before it starts, as described in its configuration documentation. Metabase's open source and Starter plans cover Google sign-in and LDAP, while SAML, OIDC, JWT and SCIM require Pro or Enterprise, so an SSO requirement usually means a paid plan from the start. Redash's setup guide recommends Google OAuth for production, so verify any other provider against its current documentation. Grafana Enterprise adds SAML authentication, and the identity options for Lightdash are not covered here, so confirm them with the vendor. Plan the upkeep too: Superset needs PostgreSQL or MySQL as its metadata database plus a caching layer and Celery workers for alerts, and Redash needs PostgreSQL, Redis, an API server and a worker, with at least 4 GB of RAM recommended. Run a proof of concept that tests your SSO flow and one restricted dataset end to end.
Which BI tool fits which scenario
This table maps common BI scenarios to the platform that usually fits best, why it fits, and the condition that would change the choice. Read each row against your own data stack, user base and licensing constraints, since paid features in Metabase and the metrics focus of Grafana can shift the answer quickly.
| Scenario | Best fit | Why | When the choice changes |
|---|---|---|---|
| SQL-first analyst team on a warehouse | Apache Superset | Apache-2.0 license with no paid edition, a full SQL IDE, a no-code chart builder and a semantic layer suit analysts who write SQL daily. | If analysts want to explore without writing SQL, Metabase or Redash may fit better. Confirm the database drivers you need are supported. |
| Self-serve business users needing no-code questions | Metabase | Its question builder lets non-technical users filter and group data without SQL, and the AGPL open-source edition covers basic use. | Row and column level permissions, SSO and usage analytics are paid Pro or Enterprise features, so budget for them if business users need governed access. |
| Team that needs SSO and row-level security without paying | Apache Superset | OAuth2 providers, LDAP and AUTH_ROLES_MAPPING are part of the Apache-2.0 build, with no paid edition required for these controls. | Confirm the row-level security model meets your rules, and plan for the upkeep of the Flask-AppBuilder stack and its metadata database. |
| dbt-centric modeling team | Lightdash | It is built around dbt models and metrics, so analysts define business logic once in the transformation layer and reuse it in charts. | If you need a broad SQL IDE or non-dbt sources as the main workload, Superset or Metabase are a better match. Confirm current dbt integration details with the vendor. |
| Operational or metrics dashboards | Grafana | It is built to query, visualize, alert on and explore metrics, logs and traces wherever they are stored, which suits monitoring rather than business analysis. | Grafana is AGPL-3.0-only, and SAML authentication, reporting and auditing sit in Grafana Enterprise. For business reporting on warehouse tables, Superset or Metabase usually fit better. |
| Embedding BI in a product | Metabase | Its embedding documentation covers embedding in customer-facing applications, and embedding without Metabase branding is a paid Pro or Enterprise feature. | If you need white-label embedding at low licensing cost, confirm terms with Metabase and compare with Superset, which has no paid edition. Plan upgrades and sizing for any customer-facing tier. |
Each option in brief, with its license
Five self-hosted options sit on this shortlist, and each ships under a different license model. Apache Superset and Redash use permissive licenses, Metabase and Grafana use AGPL terms with separate commercial editions, and Lightdash needs its terms confirmed before you compare costs.
Apache Superset: Apache-2.0, no paid edition
Apache Superset is licensed under Apache-2.0 with no paid edition, so the feature set is the same whether you buy support or run it yourself. It pairs a no-code chart builder with a SQL IDE and a semantic layer, and it connects to SQL-speaking databases. It fits teams where analysts want SQL depth and the platform team can run a metadata database, a caching layer and Celery workers for alerts and reports. Check the upgrade path, since the project advises backing up the metadata database and testing in staging first.
Metabase: AGPL edition plus paid plans
Metabase ships an AGPL open-source edition alongside Commercial License editions, and its Pro and Enterprise plans hold SSO, row and column permissions, and embedding without Metabase branding. It fits organizations where business users need self-serve questions and you are prepared to pay for those controls. Check the application database early: the open-source build starts on an embedded H2 database, and the documentation recommends PostgreSQL for production. Confirm which identity protocols your provider requires, because some of them sit only in the paid plans.
Redash: BSD-2-Clause with a long gap
Redash is BSD-2-Clause licensed and connects to more than 35 SQL and NoSQL sources, with a query editor, alerts, scheduled refreshes and a REST API. Its release history has a long gap: after v10.1.0 in November 2021, the next release was v25.1.0 in January 2025. It fits a SQL-first team that wants a lightweight tool, provided that team reviews the maintenance record and its security advisories before committing. Self-hosting needs PostgreSQL, Redis, and API and worker processes, with at least 4 GB of RAM recommended.
Lightdash: dbt-centric dashboards
Lightdash is included here for teams whose metrics already live in a dbt project, so dashboards are built on models and measures that engineers maintain in code. Confirm its license, edition terms and self-hosting requirements with the project before you compare costs. It fits organizations where the dbt project is the agreed source of metric definitions. Check whether those definitions match how finance and operations already name their measures, since a mismatch creates duplicate numbers on dashboards.
Grafana: AGPL-3.0-only with Enterprise
Grafana has been AGPL-3.0-only since version 8.0, relicensed from Apache-2.0 on April 20, 2021, and Grafana Enterprise is a separate commercial edition with SAML authentication, reporting and auditing. It queries, visualizes and alerts on metrics, logs and traces wherever they are stored, so it suits operational dashboards more than business self-serve BI. Review AGPL obligations with your legal team before modifying or distributing it, and confirm which Enterprise features you need before choosing that edition.
What the paid editions unlock in Metabase and Grafana
Metabase keeps its open source edition free, but several controls that many regulated teams need sit behind paid plans. The pricing page places these features in Pro and Enterprise only, so a team that needs them should budget for a plan before sharing its first dashboard. Check each item against your access model before assuming the open source build covers it.
- SSO beyond Google and LDAP: JWT, OIDC and SAML, including documented setups for Auth0, Entra ID, Google, Keycloak and Okta, require Pro or Enterprise. Open source and Starter support Google sign-in and LDAP.
- Row and column permissions: Restricting which rows and columns each group can see is a paid feature. This matters when one database serves several business units with different data rights.
- Multi-tenant data segregation: Keeping tenants' data separated within one Metabase instance is included only in Pro and Enterprise.
- Usage analytics and auditing: Tracking who ran which queries and changed which content is a paid feature, which matters for access reviews and evidence requests.
- Embedding without Metabase branding: Removing Metabase branding from embedded dashboards is listed for paid plans. Advanced LDAP group sync and SCIM provisioning also require Pro or Enterprise.
Confirm with Metabase which plan includes each control you need, because this feature split is the main driver of licensing cost.
The Metabase pricing page lists four plans: Open Source, Starter, Pro and Enterprise. Open Source is free. The published figures below cover the two self-serve paid plans, and Enterprise is priced by quote. Per-user add-ons apply once a plan's included user count is exceeded, so headcount and plan choice together set the monthly bill.
- Starter: $100 per month, or $90 per month billed yearly, with the first 5 users included, according to the Metabase pricing page.
- Pro: $575 per month, or $517.50 per month billed yearly, with the first 10 users included.
- Additional users: $6 per month per user on Starter and $12 per month per user on Pro.
- Enterprise: priced by quote starting at $20,000 per year, so the written quote defines scope, support and included features.
- Recurring and one-time costs: Subscription fees recur. Hosting, the PostgreSQL application database, backups and upgrade work also recur, and the initial setup is typically a one-time effort for your team or the partner you engage.
Ask for any quote in writing with your user count, billing term and included features, and confirm that the figures match the pricing page on the day you buy.
Grafana has been licensed under AGPL-3.0-only since version 8.0, after it relicensed from Apache-2.0 on April 20, 2021. Grafana Enterprise is a separate commercial edition, so its enterprise capabilities come from a different product build and agreement rather than from the open source download. Grafana is built to query, visualize, alert on and explore metrics, logs and traces wherever they are stored, and the Enterprise edition adds controls for identity, reporting and audit.
- SAML authentication: Grafana Enterprise lists SAML authentication as a feature. This matters when your identity provider issues SAML assertions and you do not want a separate OIDC integration.
- Reporting: The Enterprise edition includes reporting features. Confirm the exact report formats, delivery methods and access controls in the current documentation before you plan around them.
- Auditing: Enterprise includes auditing, which can support access evidence requests. Confirm which events are logged, where they are stored and how long they are retained.
- License terms: AGPL-3.0 obligations can apply to modified versions you distribute or offer to users over a network. Have counsel review your plan before modifying or embedding Grafana.
- Contract scope: Enterprise pricing and terms come from Grafana Labs, so request the written scope, support terms and license definitions before you compare costs.
Confirm with Grafana Labs exactly which Enterprise features your contract includes, since the features named here are examples drawn from the product's published edition summary.
Apache Superset is licensed under Apache-2.0, and the project has no paid edition. Redash is licensed under BSD-2-Clause, and the open source edition is the only one described here. Both can be self-hosted at no license fee, so the cost question shifts to who supports the platform, how upgrades are handled and what your team must operate.
- Superset license: Apache-2.0 permits commercial use and modification. Upgrades, backups and security response remain your responsibility unless a provider takes them on under contract.
- Redash license: BSD-2-Clause is a permissive license with a short notice requirement. Confirm the terms with your legal team if you plan to redistribute modified builds.
- Core features: Superset's SQL IDE and no-code chart builder, and Redash's query editor, alerts and REST API, are not listed as paid features in the sources reviewed. Verify this in the current documentation before you commit.
- Managed or support offerings: Ask Apache Superset's commercial service providers and Redash's maintainers directly whether managed hosting or support contracts exist and what they cover.
- Operating load: Superset upgrades call for a metadata database backup and staging tests, and Redash needs PostgreSQL, Redis and worker processes, so plan operations work for either tool.
Confirm managed or support offerings with each vendor before you assume they exist, and get any support scope, response commitments and upgrade responsibilities in writing.
How the self-hosted architecture changes your upkeep
Start with the metadata store, because it decides how much infrastructure you own on day one. Apache Superset needs a metadata database for production, and the architecture documentation tests PostgreSQL and MySQL for that role and does not recommend the SQLite default used by Quickstart and PyPI installs. The configuration documentation lists PostgreSQL 10 to 17 and MySQL 5.7 and 8.x as supported versions, so check those against your database standard before you pick a version. Alerts and reports, async queries and dashboard thumbnails add a caching layer and Celery worker and beat processes, which in most installations means Redis and Celery. If you do not need those features, you can run without them, but you should confirm that your dashboard refresh and scheduling needs are met without workers. For Kubernetes, note that current development docs mark the official Helm chart as deprecated and point new deployments to the Apache Superset Kubernetes Operator, so confirm the install path with your platform team before you write deployment code.
Metabase ships with an embedded H2 application database, which is fine for a demo and a poor fit for production. The docs recommend PostgreSQL for production, and they also support MySQL 8.4.0 or MariaDB 10.6.0 and later with utf8mb4. If you start on H2 and later move, Metabase documents a one-time load-from-h2 command, and it must run with the same Metabase version that last wrote the H2 file. Plan that migration as a dated change with a rollback point, not as a later tidy-up. Upgrades run application database migrations automatically, so back up the application database first, and for major upgrades the docs say to reduce a cluster to a single node because of a migration lock. Metabase 64 is an LTS release with support until December 1, 2027, which gives you a clearer upgrade calendar than non-LTS lines that reach end of life after about two months.
Redash has the most components to keep alive. A self-hosted deployment needs PostgreSQL, Redis, the API server and background workers, and the setup guide recommends at least 4 GB of RAM. Ask who owns each process, how workers are restarted after a failure, and how Redis persistence is handled, since scheduled refreshes and alerts depend on the workers. The guide also recommends a mail server, Google OAuth, HTTPS and a set of environment variables for production, so budget time for those items alongside the core services. Because Redash's release history had a long gap between v10.1.0 in November 2021 and v25.1.0 in January 2025, ask your team to confirm the release cadence it expects before committing to the stack.
Keeping each BI tool upgraded without breaking dashboards
The sequence protects dashboards, saved queries and user access by making every upgrade reversible and tested before it touches production, with the same steps applied to Superset and Metabase where their mechanics differ.
Back up the metadata and application databases
Before any upgrade, the platform owner takes a backup of the metadata database that holds Superset dashboards, charts, users and roles, or the Metabase application database that holds questions, dashboards, permissions and settings. Both tools run schema migrations during upgrades, so the backup is the only reliable way back if a migration fails. The step is done when the team has a restore test on a separate host, not just a dump file that has never been read back.
Read the release notes for breaking changes
For Superset, the team reads UPDATING.md in the repository for every version between the current and target release, since breaking changes are recorded there. For Metabase, the team checks the upgrade guidance and the version support page to confirm the target release and its end-of-life date. Owners of dashboards that use custom SQL, embedding or authentication mappings should flag those items for testing. The step is done when a written list of affected features is agreed by the platform owner and a BI lead.
Rehearse the upgrade in a staging environment
The team restores the production backup into a staging instance running the same configuration, then performs the upgrade there using the same images, configuration files and secrets as production. They confirm that Superset's SECRET_KEY handling and any PREVIOUS_SECRET_KEY setting still apply, and that caching, alerts and report workers come back up. The step is done when staging starts cleanly and the team has a timed, documented run that production can repeat.
Validate critical dashboards and access paths
A named BI owner picks a short list of high-use dashboards, scheduled reports, embedded views and SSO or LDAP logins, then compares their results and permissions before and after the staging upgrade. Row and column permissions, group-to-role mappings and data source connections are the items most likely to change silently. The step is done when every item on the list has been checked against the pre-upgrade results and any differences are logged and resolved.
Reduce Metabase clusters to one node for major upgrades
For Metabase major upgrades, the platform owner scales a clustered deployment down to a single node, because the documented application database migration uses a lock that other nodes would conflict with. Teams on versions older than 40 also upgrade one release at a time rather than jumping directly. The step is done when the cluster is at one node, the migration has completed on that node and the team has confirmed the version reported by the application.
Run the Superset database upgrade and initialization
On the production Superset host, the operator deploys the tested version, then runs the documented database upgrade command followed by the initialization command, using the same configuration as staging. Workers and the caching layer are restarted after the schema change so that alerts, reports and thumbnails use the new code. The step is done when the application starts, the migration log shows no errors and a smoke test of a dashboard query succeeds.
Confirm dashboards and keep a rollback path
After production is upgraded, the BI owner repeats the validation list from staging, checks scheduled reports and alert deliveries, and watches logs for the first business cycle. The backup and the previous application image stay available until the owners agree the upgrade is stable. For Metabase, the team also records the support window, noting that Metabase 64 is an LTS release published on September 16, 2026 with end of life on December 1, 2027, while non-LTS releases usually reach end of life after 2 months. The step is done when the sign-off is recorded and the next upgrade date is set against the vendor's support calendar.
Questions buyers ask before choosing and hosting BI
Does Apache Superset have a paid edition?
No. Apache Superset is released under the Apache License 2.0 and the project has no paid edition, so the software itself carries no license fee. Costs come from the infrastructure it runs on, the metadata database, the caching layer and optional Celery workers, plus the staff time to operate them. Any commercial support or managed hosting is sold by third parties, so ask each provider what it covers and confirm terms in writing before you rely on it.
What does Metabase Pro cost, and what drives the per-user price?
The Metabase pricing page lists Pro at $575 per month, or $517.50 per month billed yearly, with the first 10 users included. Additional Pro users cost $12 per month each, so the number of named users is the main driver. Enterprise is priced by quote, starting at $20,000 per year. Pro is also the plan that includes SSO, row and column level permissions and embedding without Metabase branding, so check which of those you need before you size the plan. Confirm current prices on the pricing page at the time of purchase.
Is Google sign-in or LDAP enough for single sign-on in Metabase?
It depends on how you assign access. The open source and Starter plans support Google sign-in and LDAP. JWT, OIDC, SAML with documented setups for Auth0, Entra ID, Google, Keycloak and Okta, advanced LDAP group and attribute sync and SCIM provisioning require Pro or Enterprise. If you need automated provisioning or group-based role mapping from an enterprise identity provider, plan for Pro or Enterprise. If a simple login with a known user list is enough, the lower tiers may suffice. Confirm the exact sign-in flow with Metabase before committing.
How much effort does a self-hosted Redash or Superset need, and who owns it?
Both need a team that owns the stack after go-live. Redash needs a PostgreSQL database, Redis, an API server and background workers, with a documented minimum of 4 GB of RAM, plus a mail server, Google OAuth and HTTPS for production. Superset needs a metadata database (PostgreSQL 10 to 17 or MySQL 5.7 or 8.x), a required SECRET_KEY, and, for alerts, reports, async queries and thumbnails, a caching layer and Celery workers, with Redis and Celery used in most installations. The team must own backups, upgrades, connections to data sources, user access and monitoring. Ask a partner to scope these in writing before you size staffing.
How long does an upgrade take, and what drives the time?
No fixed duration is supplied for either tool, so the answer depends on your environment, version gap and testing. For Superset, the documentation says to back up the metadata database, run superset db upgrade and superset init, test in staging first and read UPDATING.md for breaking changes. For Metabase, upgrades run application database migrations automatically, the docs recommend backing up first, and a cluster should be reduced to a single node for major upgrades because of a migration lock. Versions older than 40 require stepwise upgrades. Plan a staging rehearsal and confirm timing against your own environment.
Do Lightdash or Grafana replace a BI tool?
Only for some jobs. Lightdash is built around dbt models, so it fits teams whose metrics already live in dbt and who want dashboards tied to that layer. Grafana is built to query, visualize, alert on and explore metrics, logs and traces wherever they are stored, which suits operational dashboards more than ad hoc business reporting. Grafana is licensed AGPL-3.0-only, and features such as SAML authentication, reporting and auditing sit in Grafana Enterprise. If your users need self-serve analysis across business data, compare them against Superset or Metabase on the same data sources before deciding.
Can DeployOpen implement and host one of these BI stacks for us?
Yes, DeployOpen plans, implements, customizes, integrates, hardens, backs up, upgrades, documents and supports self-hosted open-source platforms inside your own cloud accounts, data centers or air-gapped networks. Most engagements are fixed-scope, with scope, deliverables and timelines agreed in writing before work starts, and ongoing support and upgrades are available as retainers. DeployOpen does not publish a price list, so a quote follows from the written scope. Ask for the scope to name the tool, identity integration, data sources, backup and upgrade responsibilities.
How DeployOpen scopes BI implementation work
DeployOpen plans, implements, integrates, hardens and documents self-hosted BI platforms inside your own cloud accounts, data centers or air-gapped networks. Engagements are fixed-scope, so the platform choice, data sources, identity model and handover items are agreed in writing before work starts.
How we scope
- Confirm which BI platform fits the team's SQL skills, no-code needs and embedding plans
- List every source database, warehouse and dbt project the dashboards must read
- Agree the identity model, including which SSO or LDAP groups map to BI roles
- Record the license edition needed for SSO, row-level permissions and embedding
How we build
- Deploy the application database, cache and workers in your infrastructure, with the metadata store sized for production
- Configure SSO, role mapping, data source connections and HTTPS according to the agreed scope
- Test dashboards, scheduled reports and alerts against staging copies before any cutover
- Run security tests on the BI deployment and its connections to the data sources it reads
How we hand over
- Document the architecture, configuration keys, secrets handling and backup procedure for your team
- Provide an upgrade runbook covering database backups, migration steps and staging tests
- Walk through the admin, data source and user management tasks with the people who will run it
- Deliver evidence for compliance assessments in the form your auditors have asked for
How we support
- Offer ongoing support, upgrades and continuous testing as a retainer after handover
- Track vendor release and end-of-life dates so upgrades are planned before support lapses
- Confirm each upgrade against the vendor's breaking-change notes in a staging environment first
- Quote retainer scope from the written requirements, with recurring effort set out in advance
