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Knowi vs Power BI: Best BI Platform for NoSQL and Multi-Source Data in 2026?

Choose Knowi if Your data lives in MongoDB, Elasticsearch, or Cassandra and you need native NoSQL querying, cross-source joins, private AI, and multi-tenant embedded analytics without ETL.
Choose Power BI if Your organization runs on Microsoft 365 and Azure with SQL-only data, and you need affordable per-user BI with deep Microsoft ecosystem integration.

Knowi natively connects to MongoDB, Elasticsearch, Cassandra, and dozens of other NoSQL and API sources without ETL, then lets you join them with SQL databases in a single query. Power BI is fundamentally SQL-oriented, requires third-party connectors or ETL pipelines for NoSQL data, and its Copilot AI sends data through Microsoft's cloud.

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AT A GLANCE

Things to Know Before You Decide

Knowi connects natively to MongoDB, Elasticsearch, Cassandra, DynamoDB, and InfluxDB. Power BI has no native connector for MongoDB Community Edition, Elasticsearch, or Cassandra and requires ODBC drivers, third-party connectors, or ETL into a SQL warehouse.

Knowi's Private AI processes data entirely inside your deployment. Power BI Copilot routes data through Microsoft's Azure OpenAI Service, which may conflict with strict data residency and privacy requirements.

Knowi handles nested JSON natively. Power BI requires custom Power Query M functions or Python scripts to flatten deeply nested JSON before it can be analyzed.

Power BI's on-premises offering (Report Server) is a significantly limited product: no dashboards, no shared datasets, no Copilot, no AI features. Knowi's on-premises deployment has full feature parity with its cloud version.

Knowi's embedded multi-tenancy is a built-in platform capability. Power BI's multi-tenancy has hard limits: 1,000 workspaces per identity, 10GB dataset limits for RLS-based isolation, and Microsoft's own documentation warns it is "susceptible to data leakage through developer error."

SIDE BY SIDE

Knowi vs Power BI at a Glance

Capability Knowi Power BI (Microsoft)
Native NoSQL Connectivity Direct connectors to MongoDB, Elasticsearch, Cassandra, DynamoDB, InfluxDB, and 30+ sources including REST APIs No native connector for MongoDB Community, Elasticsearch, or Cassandra. Atlas-only connector for MongoDB Atlas. Third-party ODBC or ETL required
Nested JSON Handling Handles deeply nested, semi-structured JSON natively without any transformation step Requires custom Power Query M functions or Python-based ETL for flattening
Cross-Source Joining Join MongoDB + PostgreSQL + REST API results in a single query with no data staging Composite models force many-to-many cardinality. 1M row cap from cloud sources, 4-min timeout
AI and NLP Private AI runs on-prem with GPU acceleration. NLQ on unmodeled data. Document AI for PDFs and Word files Copilot requires Fabric F2 (~$263/mo). Data processed through Azure OpenAI Service
Embedding Full white-label with three integration methods. Native multi-tenancy with RLS included "Embed for customers" mode via iframe. Multi-tenancy: 1,000 workspace cap or 10GB RLS limit
Multi-Tenancy Built-in multi-tenant architecture as a core platform feature 1,000 workspace cap per identity. RLS: 10GB limit, "susceptible to data leakage" per Microsoft docs
On-Premises Deployment Full-featured on-prem with complete parity to cloud, including AI with GPU acceleration Report Server: no dashboards, no shared datasets, no Copilot, no AI, no dataflows
Setup Time Days to weeks for production deployment including embedded scenarios Weeks to months depending on data modeling, gateway config, and capacity provisioning
Ecosystem Integration Source-agnostic. Connects to any database, API, or file regardless of cloud vendor Deeply integrated with Microsoft 365, Azure, Teams, SharePoint, and Fabric

BEST FIT

Who Should Choose Knowi

  1. Your data includes MongoDB, Elasticsearch, Cassandra, or other NoSQL databases.
  2. You need to join NoSQL and SQL data without building pipelines.
  3. Data privacy for AI is a hard requirement.
  4. You need full-featured on-premises BI
  5. You are embedding analytics in a multi-tenant SaaS product.
  6. You work with unstructured documents alongside structured data.

HOW CLIENTS SUCCEED WITH KNOWI

Who's Using Knowi

MacroFab

Electronics Manufacturing

Directly evaluated Power BI alongside Domo and Sisense. Manufacturing data lived in MongoDB- Power BI required months of ETL to flatten it. Knowi connected natively and went live in weeks.

Medical Device Manufacturing

Medical Devices

Analyzes QA data across their device fleet with Knowi + MongoDB tracking performance metrics, failure patterns, and compliance indicators at scale. No Power Query ETL needed.

Frequently Asked Questions

Is Power BI really cheaper than Knowi?
On per-user licensing, yes. Power BI Pro at $14/user/month is the lowest per-seat cost in enterprise BI. However, total cost of ownership depends on your data sources. If you need to connect to MongoDB, Elasticsearch, or other NoSQL databases, Power BI requires third-party connectors ($500-$5,000/year each), ETL tools, staging databases, and engineering time to build and maintain pipelines. These costs can exceed the licensing savings.
Can Power BI connect to MongoDB?
Partially. Power BI has an Atlas connector for MongoDB Atlas (cloud-hosted) only. For self-hosted MongoDB or MongoDB Community Edition, there is no Microsoft-provided connector. You need a third-party ODBC driver from vendors like CData or Progress. Knowi connects natively to all MongoDB deployments using MongoDB's own query language.
How does Copilot compare to Knowi's Private AI?
Copilot generates reports, DAX queries, and visualizations from natural language. It works well on well-modeled data with descriptions and synonyms configured. However, it processes data through Microsoft's Azure OpenAI Service. Knowi's Private AI runs entirely inside your deployment with no external data transmission, works on unmodeled data, and includes Document AI for querying PDFs and Word files. The trade-off is between Microsoft's AI infrastructure investment versus Knowi's data privacy guarantees and unmodeled data support.
Is Power BI's on-premises version a viable alternative?
Power BI Report Server is significantly more limited than Power BI Service. It lacks dashboards, shared datasets, dataflows, paginated report subscriptions, Copilot, and AI features. Microsoft positions it as a transitional solution for organizations moving to the cloud, not as a long-term on-premises BI platform. Knowi's on-premises deployment includes every feature available in its cloud version, including Private AI with GPU acceleration.
Can Power BI handle multi-tenant embedded analytics at scale?
With limitations. Workspace-based isolation caps at 1,000 workspaces per service principal. RLS-based isolation has a 10GB dataset limit and Microsoft warns about data leakage risk from misconfiguration. For SaaS products with a small number of large tenants, Power BI embedding can work well. For products with hundreds or thousands of tenants, the architectural constraints become significant. Knowi's multi-tenancy was designed for large-scale embedded scenarios from the ground up.
Why did Power BI raise prices by 40% in 2025?
Microsoft increased Power BI Pro from $10 to $14/user/month and PPU from $20 to $24/user/month in April 2025, citing the addition of Fabric and AI capabilities. Even after the increase, Power BI remains the most affordable per-user BI license. However, the increase signals that Microsoft is moving toward a model where advanced features require Fabric capacity purchases on top of per-user licensing, which raises the effective cost for teams that need AI and advanced analytics.

Skip the Warehouse. Query NoSQL and SQL Together in One Platform.

Native NoSQL connectivity, cross-source joins, Private AI, and multi-tenant embedding without the ODBC drivers, ETL pipelines, and Fabric capacity costs that Power BI requires.

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