Knowi vs Metabase: Which Embedded Analytics Tool Handles NoSQL Data?
Metabase makes it easy to build dashboards on SQL databases. Knowi natively queries NoSQL, supports cross-source joins, and bundles Private AI with embedded analytics.
Your data lives in MongoDB/Elasticsearch and you need embedded analytics with multi-tenancy, cross-source joins, and private AI.
You need free internal dashboards on a single SQL database for an internal team.
Things to Know Before You Decide
- Knowi has a semantic layer, built over live sources. Each metric and business definition lives once in governed datasets that can join SQL, NoSQL and REST API data at query time, and Knowi's AI agents answer from those definitions. There is no warehouse to build and no separate modeling project before you start. Metabase's models and metrics stay within one database, and its Library is a Pro and Enterprise feature. How the semantic layer works.
- Metabase cannot join data across different databases. Knowi joins MongoDB + PostgreSQL + Elasticsearch + REST APIs in a single query without data movement.
- Metabase has no connectors for Elasticsearch or Cassandra. Knowi natively connects to both.
- Metabase's row-level security requires Pro or Enterprise and supports rows but not columns on MongoDB. Knowi provides row-level security across all connected sources including NoSQL.
- Metabase's open source edition carries a "Powered by Metabase" watermark that can only be removed with a paid plan or by releasing your app under the AGPL. Full white-label requires Pro or Enterprise.
- Metabase's AI (Metabot) needs your own AI provider key when self-hosted, works best in English, and checks only the first 100 tables when no table is named. Knowi AI is the default model, so inference is not routed to a third-party LLM unless you enable one.
Knowi vs Metabase at a Glance
Who Should Choose Knowi
- SaaS embedded analytics at scale: Embed analytics for hundreds of customers with per-tenant data isolation, white-label branding, and no per-user pricing that scales with growth.
- MongoDB or Elasticsearch as primary data stores: Your application data lives in NoSQL databases and you need analytics that query it directly, not through a sampled schema scan.
- Cross-source analytics: A single dashboard needs data from MongoDB, PostgreSQL, and a REST API joined together. Knowi does this without building a data warehouse.
- Private AI for regulated industries: Compliance requirements prohibit sending data to cloud AI services. Knowi AI is the default model, so inference is not routed to a third-party LLM unless you enable one.
- Document analysis: Users need to query PDFs, contracts, or regulatory filings alongside structured data. Document AI with source attribution.
- MongoDB row-level security: RLS on MongoDB data for multi-tenant analytics. Metabase's RLS on MongoDB covers rows only, on Pro/Enterprise. Knowi's covers all sources.
If price drives your decision, compare directly: see Knowi pricing. For the broader field, here is the full list of Metabase alternatives.
What Our Customers Say
Retirement Planning Software
Moved off GoodData because it couldn’t natively connect to MongoDB. With Knowi, they embed a self-service dashboard builder directly in their platform, no ETL, full white-label, dark mode CSS support.
3PL Shipping Logistics Company
Embeds shipment metrics directly into their customer portal. Customers see real-time visibility into deliveries and logistics KPIs, powered by MySQL with no additional data infrastructure.
BI takes you to insight. Apps take you to outcomes.
Agents in the data layer
Knowi queries SQL, NoSQL and REST APIs where they live and joins them at query time into governed datasets. Those datasets are the layer the agents answer from, so there is no warehouse to build first.
Operational apps on your governed data
Describe the workflow in plain English, and Knowi builds the app your team does the job in, running live on the data you already trust. Each app is hosted on its own URL with its own sign-in.
Frequently Asked Questions
Is Metabase really free?
The open-source edition is free to download and self-host. However, it lacks interactive embedding, the embedding SDK, SAML SSO, and row-level security. Embedded content carries a "Powered by Metabase" watermark. Self-hosting requires infrastructure and ongoing maintenance. For production SaaS embedding, most companies need Pro ($575+/month) or Enterprise ($20,000+/year).
Can Metabase connect to Elasticsearch or Cassandra?
No. Metabase has no official connectors for Elasticsearch or Cassandra. Community-built drivers may exist but are not officially supported or maintained. Knowi has native connectors for both with live querying.
Can Metabase join data from different databases?
No. Metabase sends queries to individual databases and cannot join results across different connections. If you need to combine data from MongoDB and PostgreSQL, you must consolidate the data into a single database outside of Metabase first.
Does Metabase support row-level security on MongoDB?
Yes, on Pro and Enterprise, but only at row level. Metabase does not support column-level security on MongoDB, and row security does not apply to native queries. Knowi provides row-level security across all connected sources, including MongoDB and Elasticsearch.
How does Metabase's AI compare to Knowi's?
Metabase's Metabot is included on all plans and handles natural language queries, working best in English; when no table is named it checks only the first 100 tables. Self-hosted deployments need your own AI provider API key. Knowi's NLQ works across all data sources without pre-modeling, Document AI handles unstructured files, and Knowi AI is the default model, so inference is not routed to a third-party LLM unless you enable one.
What happens to Metabase pricing as embedded users grow?
Metabase Pro charges $12/user/month beyond the initial 10 users. Every customer user signed in to embedded analytics counts (guest embeds do not). At 500 users: ~$69,910/year. At 1,000 users: ~$134,910/year. Knowi's embedded analytics pricing does not follow a per-end-user model, making costs more predictable as your customer base grows.
See How Knowi Handles MongoDB Without the 200-Row Schema Limit
Native NoSQL querying, real multi-tenancy, and Private AI, without per-user pricing that scales with your customer base.
Led by a solutions engineer, not a sales rep
- What you'll see in the demo
- Live demo tailored to your data stack and use case
- Native MongoDB, Elasticsearch, and REST API connectivity
- AI agents querying your data and building dashboards in plain English
- How teams embed analytics into their own products
- Pricing and deployment options (cloud or on-prem)
“My team tested various data visualization tools like PowerBI, Domo, Sisense and Knowi emerged as the top choice for its speed in creating useful dashboards and ease of use for non-technical users. Knowi's architecture models data thoughtfully, which I'd credit for enabling a collection of elegant features.”
VP Business Intelligence, MacroFab
See How Knowi Handles MongoDB Without the 200-Row Schema Limit
Native NoSQL querying, real multi-tenancy, and Private AI, without per-user pricing that scales with your customer base.
- Live demo tailored to your data stack and use case
- See native MongoDB, Elasticsearch, and REST API connectivity
- Watch AI agents query your data and build dashboards in plain English
- Learn how teams embed analytics into their own products
- Get pricing and deployment options (cloud or on-prem)
Phil Bryant
VP Business Intelligence, MacroFab
