Best BI and reporting tools for MongoDB (2026): 9 tools compared on live queries, nested data, and security

The best BI tools for MongoDB in November 2026 split into two groups. MongoDB Atlas Charts, Metabase, Knowi, Grafana, and Chartbrew query collections natively in MongoDB’s own query language, while Power BI and Tableau connect through MongoDB’s Atlas SQL Interface now that the old BI Connector has reached end of life. Atlas Charts is the default for Atlas users who want free dashboards, Metabase suits teams that want a query builder their non-technical users can handle, and Knowi suits teams that need to join MongoDB with SQL sources without ETL. Qlik and Basedash work from a copy of the data instead of live queries.

The choice usually comes down to three questions: does the tool read nested documents and arrays without a flattening project, does it query live or from a copy, and can it restrict rows per viewer.

How we evaluated MongoDB reporting tools

We checked each vendor’s official documentation and pricing pages on November 15, 2026, against five criteria:

1. Connection path: native MongoDB queries, the Atlas SQL Interface, or a sync into a warehouse.
2. Nested data: how the tool handles embedded objects and arrays, the most common reason MongoDB dashboards break.
3. Query model: live queries against the cluster, cached results, or scheduled loads into another store.
4. Security: row-level filtering per viewer, SAML SSO, and SCIM provisioning.
5. Price and deployment: a published starting price, a trial, and whether you can self-host.

Why the BI Connector end of life changes the shortlist

MongoDB’s archived documentation now states that “as of September 2026, the BI Connector for Atlas and on-premises reached end-of-life” (MongoDB Connector for BI). Any SQL-only BI tool that used the mongosqld proxy needs a new path.

That path is the Atlas SQL Interface, which gives “live, read-only access” through JDBC and ODBC drivers using MongoSQL, a SQL-92 compatible dialect. You can deploy it three ways:

• On an Atlas dedicated cluster: M10 and above, MongoDB 6.0 or later. No federated database instance is required on this path.
• Through an Atlas federated database instance: no cluster tier requirement, billed at $5 per TB scanned with a 10 MB minimum per query (MongoDB pricing).
• On self-managed Enterprise Advanced: MongoDB Enterprise 6.0 or later. Community Edition clusters are not supported.

If you run Community Edition, the realistic options are a tool with a native MongoDB connector or a sync into a SQL warehouse. Our guide to connecting MongoDB to a BI tool covers the schema and replica-set decisions behind each path.

MongoDB BI tools compared

Five of the nine tools read MongoDB without SQL translation, and only two of those, Atlas Charts and Metabase, combine a native connection, a published price, and per-viewer row filtering.

MongoDB Atlas Charts: best for Atlas users who want free dashboards

Best for: teams already on Atlas that want dashboards, embeds, and email reports without buying another tool. Not ideal for: self-managed MongoDB, or dashboards that combine MongoDB with other databases.

• Pricing: “Charts is included on all Atlas clusters, with premium features available on Dedicated and Flex clusters,” and Atlas usage is billed separately (MongoDB pricing). On free M0 clusters, dashboards auto-refresh every 4 hours and manual refresh is unavailable (Charts pricing). Verified November 2026.
• Data and query model: reads clusters, federated database instances, and Online Archives in the same Atlas project (data sources). Each chart reads a single collection. Dashboards refresh when data is an hour stale by default, configurable from 1 minute to 30 days (dashboard refresh).
• AI: Natural Language Charts builds a chart from a prompt of up to 500 characters, using Azure OpenAI Service. A project owner can turn it off.
• Security: dashboard roles are viewer, author, and owner, and Atlas org SSO applies to dashboard viewers (permissions). Authenticated embeds can inject a filter per user, which works as row-level security for customer-facing charts.
• Embedding and delivery: an Embedding SDK or iframe, with Google or custom JWT authentication. Scheduled reports go by email only, up to 100 per project on Flex and M10+ clusters.
• Tradeoff: Charts is Atlas only, and MongoDB staff confirm the on-premises version was discontinued in 2021. There is no join across collections inside a chart, so cross-collection metrics need a view or an aggregation pipeline first.

Metabase: best for non-technical users on a native connection

Best for: startups and mid-size teams that want a click-through query builder on MongoDB, with an open-source option. Not ideal for: teams that want AI to write MongoDB queries, or column-level restrictions.

• Pricing: open source is free to self-host; Starter is $100 per month for 5 users plus $6 per extra user; Pro is $575 per month for 10 users plus $12 per extra user; Enterprise starts at $20,000 per year (Metabase pricing). 14-day trial on Cloud Starter and Pro. Verified November 2026.
• MongoDB support: the MongoDB driver supports Atlas SRV strings, SSL, and SSH tunnels. The query builder converts every question into a MongoDB query, and the native editor takes aggregation pipeline JSON, not SQL.
• Nested data: Metabase unfolds nested objects automatically for MongoDB but “doesn’t unfold arrays.” Schema sync samples the first and last 500 documents and up to 1,000 leaf fields per collection, so rare fields can be missed.
• AI: Metabot is on every plan, but its native query generation is SQL only (Metabot docs), so it won’t write aggregation pipelines for you.
• Security: row and column security is Pro and Enterprise only, and “MongoDB only supports row-level security.” SAML, JWT, and SCIM are Pro and Enterprise only. Connection impersonation doesn’t list MongoDB.
• Embedding: guest embeds on every plan (with a Metabase badge on open source and Starter); the React modular embedding SDK on Pro and Enterprise.

For how Metabase compares with an AI-first tool on SQL databases, see Basedash vs Metabase.

Knowi: best for joining MongoDB with SQL sources without ETL

Best for: teams that need MongoDB, SQL databases, and APIs in one dashboard, with embedded analytics and on-premises options. Not ideal for: buyers who need a published price before talking to sales.

• Pricing: quote only; Basic, Team, and Enterprise plans are priced “based on users and deployment type” (Knowi plans). Free 21-day trial. Verified November 2026.
• MongoDB support: queries in native MongoDB syntax plus Cloud9QL, Knowi’s SQL-like post-processing language, and reads nested objects and arrays without flattening. Knowi can join across SQL and NoSQL databases.
• AI: natural language queries translate to Cloud9QL, an AI assistant can use hosted or external models (OpenAI, Anthropic, Azure AI, Bedrock), and an MCP server lets Claude or Cursor operate Knowi.
• Security: user filters for row-level security, SAML and LDAP, and SCIM 2.0 for Entra ID and Okta.
• Embedding and deployment: JavaScript API or iframe, white-label, with per-user filters in SSO embeds (an add-on on every plan). Cloud, hybrid, and fully on-premises deployments are available on every plan.
• Tradeoff: Cloud9QL is proprietary, so analysts learn one more query language.

Power BI: best for Microsoft shops with Atlas or Enterprise Advanced

Best for: organizations standardized on Microsoft 365 that run MongoDB on Atlas M10+ or Enterprise Advanced. Not ideal for: Community Edition users, or teams that don’t want to run a gateway.

• Pricing: Pro $14 per user per month and Premium Per User $24, paid yearly (Power BI pricing). Copilot needs F2 or higher Fabric capacity. Verified November 2026.
• MongoDB support: the MongoDB Atlas SQL connector is generally available, owned by MongoDB, and supports Import and DirectQuery. It requires the Atlas SQL ODBC driver, and DirectQuery needs driver version 1.2 or later (MongoDB connect docs).
• Refresh: the online setup asks you to choose a data gateway, and MongoDB documents that the Power BI gateway supports only SCRAM authentication (authentication). Plan for an on-premises data gateway if you want scheduled refresh in the service.
• Security: row-level security with DAX roles works on Import and DirectQuery models; sign-in uses Microsoft Entra ID.
• Embedding: “embed for your customers” requires an A, EM, P, or F capacity SKU.
• Tradeoff: Microsoft’s connector page still says you need a federated database instance. MongoDB’s docs show that M10+ dedicated clusters no longer do.

Tableau: best for existing Tableau teams moving off the BI Connector

Best for: analysts already licensed on Tableau who need a supported MongoDB path after the BI Connector end of life. Not ideal for: teams that want governed data policies on MongoDB, which Tableau doesn’t document for this connector.

• Pricing: Standard from $15 and Enterprise from $35 per user per month, billed annually; every deployment needs at least one Creator license (Tableau pricing). Verified November 2026.
• MongoDB support: the MongoDB SQL Interface connector is generally available in Tableau Cloud, Desktop, Prep, and Server and is bundled in Desktop and Server 2025 and later. Tableau deprecated its old MongoDB BI connector in 2025.3. Tableau Cloud supports SCRAM authentication only.
• Security: user filters map users to values for row-level security. Data policies need the Data Management license and a connector that supports virtual connections, and Tableau’s list doesn’t include the new MongoDB connector. SAML SSO and SCIM are available.
• AI: Tableau Pulse is in Standard; Tableau Agent needs Tableau+ on Cloud or Server 2025.3 with AI turned on.
• Tradeoff: MongoSQL flattens documents at query time, so calculated fields built on old BI Connector schemas may need rewrites.

Grafana: best for operational and time-series monitoring on MongoDB

Best for: engineering and ops teams that already use Grafana and want alerting on MongoDB queries. Not ideal for: business users who need a point-and-click builder, or cost-sensitive teams on Grafana OSS.

• Pricing: the MongoDB data source is an Enterprise plugin. On Grafana Cloud, it needs the Advanced plan or Pro with the Enterprise Plugins add-on; self-managed Grafana needs an Enterprise license. Cloud Pro starts at $19 per month plus usage, and Enterprise plugins cost $55 per active user per month instead of $8. Verified November 2026.
• MongoDB support: queries use mongosh syntax; only find and aggregate read commands are supported, one command per panel. Requires MongoDB 5.0 or later.
• AI and alerting: alerting works on this data source, and Grafana Assistant can generate MongoDB queries from natural language.
• Security: SAML, fine-grained RBAC, and data source permissions are Enterprise and Cloud features. There is no per-viewer row filter.
• Embedding: externally shared dashboards work with MongoDB but are read-only and don’t support variables (shared dashboards). Panel iframe embedding isn’t available on Grafana Cloud.

Qlik Cloud Analytics: best for in-memory associative analysis

Best for: enterprises already on Qlik that want MongoDB loaded alongside ERP and CRM data. Not ideal for: live dashboards on operational data, since Qlik doesn’t offer Direct Query for MongoDB.

• Pricing: Starter $300 per month for 10 users and 10 GB of data, Standard $825 per month for 25 GB, Premium $2,750 per month for 50 GB, all billed annually; Enterprise by quote (Qlik pricing). 30-day free trial. Verified November 2026.
• MongoDB support: the MongoDB connector in the ODBC Connector Package supports MongoDB 6.0, 7.0, and 8.0 and loads data into the app. MongoDB isn’t on the Direct Query source list, and Qlik’s generic ODBC connector doesn’t support the Atlas SQL driver.
• Security: section access restricts rows and columns; SAML or OIDC SSO, and SCIM with Entra ID.
• AI: Qlik Answers replaces Insight Advisor in tenants with the agentic experience.
• Tradeoff: pricing scales with data loaded, so large collections raise the bill even with few users.

Chartbrew: best low-cost option for client and KPI dashboards

Best for: small teams and agencies that want MongoDB KPI dashboards they can share with clients. Not ideal for: companies that need SSO or documented row-level security.

• Pricing: Starter $41 per month billed yearly ($490 per year), Growth $1,290 per year, Professional $3,990 per year; monthly billing costs more (Chartbrew pricing). 14-day trial, no card. Self-hosting is free under the Functional Source License, which bars offering Chartbrew as a hosted service. Verified November 2026.
• MongoDB support: a native MongoDB connection with mongosh-style queries and an AI query assistant that writes MongoDB queries from a description.
• Sharing and alerts: password-protected embeds, signed share tokens with custom parameters, client accounts with admin, editor, and viewer roles, scheduled email snapshots, and data alerts with anomaly detection to Slack, email, or webhooks.
• Tradeoff: plans cap monthly data requests (5,000 on Starter), and SSO isn’t documented.

Basedash: best for asking questions across MongoDB and SaaS data

Best for: teams that want an AI data analyst on MongoDB data joined with Stripe, HubSpot, or other synced sources, without running their own warehouse. Not ideal for: live queries against the cluster, per-viewer row-level security on MongoDB data, or self-hosted deployments of the MongoDB sync.

• Pricing: Startup is $1,000 per month plus AI usage for up to 25 users, including $1,000 per month in AI credits; Enterprise is custom (Basedash pricing). 14-day free trial, no card. Verified November 2026.
• MongoDB support: Basedash doesn’t query MongoDB directly. The MongoDB connector runs on Fivetran and syncs into Basedash Warehouse, a managed DuckDB warehouse, every 15 minutes to 24 hours (hourly by default). Each connector lands in its own schema, so MongoDB tables can be joined with other synced sources. See data ingestion.
• AI: the AI data analyst answers questions in chat, shows the SQL, and builds charts and dashboards; Insights posts scheduled findings to email or Slack. An MCP server on every plan lets Claude or ChatGPT query the same data.
• Security: row-level security is Postgres and Supabase only, so it doesn’t apply to synced MongoDB tables. Data source access control limits who sees each connector’s tables. SAML or OIDC SSO and SCIM are Enterprise features.
• Tradeoff: SaaS connectors, including MongoDB, run on Basedash Cloud only, not on self-hosted deployments. Embedding is Enterprise only.

Which MongoDB BI tool should you choose?

You run Atlas and want something today at no extra license cost. Start with Atlas Charts. It handles nested documents natively, refreshes as often as every minute on paid clusters, and embeds with per-user filters.

Your business users don’t write queries. Metabase’s query builder is the most approachable native option, and Atlas Charts’ natural language mode helps for one-off charts. Basedash suits teams that would rather ask in plain English and can work from a synced copy.

You run self-managed Community Edition. Atlas SQL isn’t available, so pick a native connector (Metabase, Knowi, Grafana, Chartbrew) or sync into a warehouse.

You need MongoDB joined with Postgres, Snowflake, or SaaS data. Knowi joins live across sources. A Fivetran or Airbyte sync into Snowflake or BigQuery opens up every SQL BI tool; Basedash does the sync and warehouse for you.

You’re replacing BI Connector dashboards in Tableau or Power BI. Move to the Atlas SQL connector for your tool. On M10+ dedicated clusters you no longer need a federated database instance.

You’re embedding MongoDB charts in a SaaS product. Atlas Charts (JWT plus injected filters), Knowi (white-label SDK), and Metabase (guest embeds or the React SDK on Pro) are the main fits. Compare more options in our embedded analytics platforms guide.

You mostly need alerts on operational metrics. Grafana, if you already pay for Enterprise plugins, or Chartbrew for a lower-cost setup with anomaly alerts.

Frequently asked questions

Which tool is best for MongoDB reporting?

It depends on where MongoDB runs and who builds the reports. On Atlas, MongoDB Atlas Charts is included at no extra license cost, reads nested documents natively, and sends scheduled email reports. For non-technical users on any deployment, Metabase’s native driver turns point-and-click questions into MongoDB queries, and the open-source edition is free. For reports that combine MongoDB with SQL databases, Knowi joins them without ETL. Power BI and Tableau work well if you already own them and can use the Atlas SQL Interface on Atlas M10+ or Enterprise Advanced.

Does MongoDB need a federated database instance to use Atlas SQL with Tableau or Power BI?

Not anymore on Atlas dedicated clusters. MongoDB’s SQL Interface docs list three deployment options: directly on a dedicated M10+ cluster running MongoDB 6.0 or later, through a federated database instance, or on self-managed Enterprise Advanced. Only the federated path needs a federated database instance, and it bills $5 per TB scanned with a 10 MB minimum per query. Microsoft’s Power BI connector page still says a federated database is required, which predates the dedicated-cluster option. Free, Flex, M2, and M5 clusters can only use the federated path.

What replaced the MongoDB BI Connector?

The Atlas SQL Interface. MongoDB’s documentation says the BI Connector for Atlas and on-premises reached end of life in September 2026 and that its docs are archived. Atlas SQL uses JDBC and ODBC drivers, a SQL-92 compatible dialect called MongoSQL, and certified connectors for Power BI (Import and DirectQuery) and Tableau (Cloud, Desktop, Prep, and Server). Queries written for the BI Connector may need changes because MongoSQL flattens nested documents differently. MongoDB’s transition guide covers the dialect differences.

Can I use Metabase with MongoDB?

Yes. Metabase has a native MongoDB driver that supports Atlas SRV connection strings, SSL, and SSH tunnels. The query builder translates questions into MongoDB queries, and the native editor accepts aggregation pipeline JSON. Nested objects are unfolded into separate fields automatically, but arrays are not. Two limits matter: Metabot’s AI query generation is SQL only, so it won’t write MongoDB pipelines, and row-level security on MongoDB requires the Pro plan ($575 per month for 10 users as of November 2026) or Enterprise.

What’s the best way to get MongoDB data into Snowflake or BigQuery for BI?

Use a managed change data capture connector. Fivetran and Airbyte both read MongoDB’s oplog or change streams and sync incrementally into Snowflake, BigQuery, Redshift, or Databricks, where any SQL BI tool can query the data and join it with other sources. Fivetran costs more but needs less maintenance; Airbyte can be self-hosted. Set sync frequency per collection, since frequent syncs raise both connector and warehouse costs. If you don’t want to run a warehouse at all, tools like Basedash run the Fivetran sync into a managed warehouse for you.

Should I run analytics directly on MongoDB or move to ClickHouse or a warehouse?

Querying MongoDB directly works for operational dashboards on a single cluster, as long as BI tools read from a secondary or an Atlas analytics node rather than the primary. Move to a columnar store such as ClickHouse, Snowflake, or BigQuery when dashboards scan months of events, join several sources, or slow down production. Most teams keep MongoDB as the application database and use CDC to copy it into the analytics store, then point BI tools there.

Which MongoDB BI tools support row-level security for customer-facing dashboards?

Atlas Charts can inject a MongoDB filter for each user viewing an authenticated embed, which restricts rows per customer. Knowi applies user filters and per-user content filters in SSO embeds. Metabase supports row-level (not column-level) security on MongoDB in Pro and Enterprise. Power BI and Tableau apply their own RLS on top of the Atlas SQL connection. Grafana only offers data source permissions, and Chartbrew relies on parameterized share tokens rather than documented row-level security.