Knowi vs Looker: A Comparison Review on Pricing, Functionality, Ease of Use in 2025

TL;DR

• Looker: Best for large, SQL-focused enterprises with Google Cloud investments. Strong governance, semantic modeling (LookML), and AI features powered by Gemini, but limited native NoSQL capabilities.
  
• Knowi: Designed for mixed SQL + NoSQL environments, real-time analytics without ETL, and minimal learning curve.
  
• Key difference: LookML complexity vs Knowi’s drag-and-drop simplicity and built-in search-based analytics.
  

Table of Contents

1. Quick Comparison Table
2. Looker: Deepdive
3. Knowi: Deepdive
4. Where Knowi Stands Out Against Looker
5. When to Choose Looker
6. When to Choose Knowi
7. Final Verdict
8. FAQs: Looker vs Knowi (2025)

When shopping for an analytics tool, it can be difficult to dissect the pros and cons without diving into a lengthy trial or POC. Here is a high level comparison between two popular enterprise data platforms, Looker and Knowi.

Quick Comparison: Looker vs Knowi

Looker

Looker, part of the Google Cloud Platform, is a modern BI and data exploration tool designed for enterprises that want a centralized, governed analytics layer. It is built for SQL-first organizations and is tightly integrated with Google’s ecosystem, offering advanced AI features via Gemini. Looker can connect to BigQuery, Redshift, and 60+ other SQL databases.

Looker Key Features (2025)

1. LookML Semantic Layer
   
   • Proprietary modeling language for defining metrics, dimensions, and relationships.
     
   • Centralizes business logic and ensures consistency across reports.
     
   • Git-based version control for collaborative development.
     
   • Requires SQL and technical expertise.
     
2. AI-Powered Features (Gemini Integration)
   
   • Conversational analytics with natural language queries.
     
   • Visualization, formula, and LookML code assistants.
     
   • Automated slide deck creation from dashboards.
     
   • Python code interpreter (preview) for advanced analytics.
     
3. Data Connectivity
   
   • Optimized for SQL warehouses: BigQuery, Snowflake, Redshift, Azure Synapse.
     
   • Supports Google Sheets, Excel, and major marketing platforms (Google Ads, Facebook Ads, GA4).
     
   • Limited native NoSQL connectivity.
     
4. Deployment Options
   
   • Google Cloud-hosted (managed service).
     
   • Self-hosted and other cloud providers.
     
   • 100% browser-based interface – no desktop install.
     
5. User Roles
   
   • Developers: Full LookML and API access.
     
   • Standard users: Limited exploration without dev mode.
     
   • Viewers: Dashboard consumption only.
     

Looker Pricing

Looker pricing and pricing structure are not listed on their website. In order to access their pricing plans, you must speak to a representative and request a quote. However, below are the plans listed on their website.

• Looker Studio – Free (basic features, no LookML).
  
• Looker Studio Pro – Subscription, monthly per-user pricing.
  
• Looker (Core Platform) – Enterprise pricing based on users, queries, and hosting.
  
• Embedding Tier – Includes 500K API query calls/month; additional usage billed.
  

Note: Pricing is opaque and often involves significant Google Cloud storage/query costs if using BigQuery.

Looker Advantages

• Enterprise-grade governance via LookML.
  
• Seamless integration with Google Cloud and marketing tools.
  
• Proven scalability with Fortune 500 deployments.
  
• Advanced AI capabilities with Gemini.
  
• Strong security, version control, and compliance.
  

Looker Disadvantages

• Steep learning curve due to LookML, the Looker specific langauge
  
• Limited native support for NoSQL.
  
• Requires a SQL warehouse for most use cases (adds cost and latency).
  
• Pricing transparency is low, making TCO estimates harder.
  
• Less flexible for ad-hoc exploration without prior modeling.

Knowi

Knowi is a unique end-to-end AI analytics platform that reduces the number of tools you need to get from data to insights. Knowi has competitive pricing, a comprehensive list of capabilities, and was designed to be as intuitive as possible. It can connect into both SQL and NoSQL databases as well as external applications such as HubSpot, Quickbooks, and Salesforce at no additional cost.

Knowi Features (2025)

• Native SQL + NoSQL + Document Analytics – Connect directly to 30+ SQL databases, NoSQL stores (MongoDB, Cassandra, Elasticsearch, DynamoDB, etc.), REST APIs, and even unstructured data like contracts or PDFs.
  
• Real-Time, No-ETL Architecture – Query data live from the source without moving it to a warehouse.
  
• AI-Powered Analytics – Secure, private AI models generate dashboards, explain trends, detect anomalies, and provide instant insights without sending data outside the Knowi ecosystem.
  
• Agentic BI – Beyond answering questions, Knowi can proactively surface insights, automate actions, and recommend next steps.
  
• Natural Language Queries (NLQ) – Ask questions in plain English across any connected data and get visual or tabular answers instantly.
  
• Cross-Database Joins – Blend SQL, NoSQL, APIs, and documents in a single real-time query.
  
• Advanced Visualizations – Custom dashboards, topology maps, geospatial views, and telco-specific network topology visualizations.
  
• Embedded Analytics – White-label dashboards in apps or portals with SSO, row-level security, and flexible embedding options.
  
• Alerts & Automation – Trigger notifications via email, Slack, Teams, or webhooks when thresholds or anomalies are detected.
  
• Enterprise-Grade Security – Role-based access, row-level permissions, and private AI deployment options.

Knowi Pricing

• Offers 3 plans  – Basic, Teams and Enterprises with discounts for startup, and non-profit.
  
• Deployment options: Cloud, On-Premises, or Hybrid.
  
• Pricing based on:
  
  1. Internal and external (embedded) user counts
     
  2. Deployment type
     
  3. Required features or add-ons (e.g., Machine Learning, Alerts, Management API)
     
• Annual subscription model with predictable, fixed pricing (no surprise usage charges).
  

Knowi Advantages

• Best-in-class NoSQL & unstructured data support — no need to ETL into a warehouse.
  
• Secure AI analytics — private small language models ensure data never leaves your environment.
  
• Agentic BI — proactive, automated insight delivery instead of only reactive dashboards.
  
• Polyglot persistence — one platform for SQL, NoSQL, APIs, and documents.
  
• Real-time joins across sources without performance-killing extracts.
  
• Business-user friendly with drag-and-drop dashboards and NLQ.
  
• Flexible deployment — on-prem, cloud, or hybrid.
  
• Telco-ready visualizations like network topology and multi-layer mapping.

Knowi Disadvantages

• Smaller brand visibility compared to larger BI vendors like Tableau or Power BI.
  
• Visualization customization depth is slightly less extensive than some specialist BI tools.

Where Knowi Stands Out Against Looker

1. Native NoSQL Support

Looker’s SQL focus means NoSQL data requires transformation.
Knowi connects directly to MongoDB, Cassandra, Elasticsearch, and 30+ other NoSQL sources—no ETL, schema flattening, or warehouse needed.

2. Lower Learning Curve

With Looker, business users often rely on technical teams to modify LookML.
Knowi enables self-service analytics with drag-and-drop dashboards and built-in natural language queries that work across all connected data.

3. Real-Time Cross-Database Joins

Looker can blend SQL sources but struggles with polyglot persistence.
Knowi can join MongoDB + PostgreSQL + REST API in a single real-time query without preloading into a warehouse.

4. Cost Efficiency

No warehouse dependency means Knowi reduces infrastructure and query costs while delivering faster insights.

5. Search-Based Analytics

Knowi’s search bar lets users explore data directly in plain English—no modeling layer required for quick questions.

When to Choose Looker

• Your entire analytics stack is SQL-based.
  
• You already have significant Google Cloud investment.
  
• You need a strict semantic layer for governance.
  
• You have a large technical/data engineering team to manage models.
  
• You rely heavily on Google marketing tools.
  

When to Choose Knowi

• You use NoSQL or a mix of SQL and NoSQL.
  
• You want to eliminate ETL pipelines.
  
• You have limited technical resources.
  
• You need real-time analytics directly from source.
  
• You want faster, more flexible exploration.

Conclusion

Knowi can work alongside other visualization tools and is quick and easy to set up. It is suitable for you if you are looking for a robust visualization/embed tool or an alternative to the one you are already using. Looker may be suitable for you if you have a team already familiar with Looker, LookML, and have the budget required for the additional tools needed for it to operate.

Depending on your specific use case and current infrastructure, these may be pros or cons for you. You can read more about Knowi here.  

If you want to see the product in action you can request a demo, or start a free Knowi trial to test it out for yourself.

If you want to compare other BI tools alternatives, see are comparison blogs which compares different BI tools and datasources and helps you arrive at the one best suited for your needs.

Related Comparisons

  – See also: PowerBI vs Knowi

  – Tableau Alternative

  – Modern vs Legacy BI Platforms

Frequently Asked Questions