How to Join MongoDB Data with MySQL, Elasticsearch, REST APIs, and Amazon Redshift
Join MongoDB with MySQL, Elasticsearch, REST APIs & Redshift—no ETL needed. Learn how to unify data & build AI-powered dashboards in minutes with Knowi.
The Ultimate Sisense Review for Business Intelligence and Analytics (2025)
Sisense offers powerful embedded analytics and high-performance dashboards—but is it built for today’s AI-native, hybrid data world? In this review, we break down where Sisense shines, where it falls short, and how it compares to modern alternatives like Knowi.
The Best MongoDB Visualization, Reporting and Analytics Tools [Updated 2025]
A guide for teams who want to build accurate MongoDB dashboards and enable efficient reporting and analysis of their data for better decision making.
Is MongoDB Good for Analytics?
Is MongoDB good for analytics? Here we show how to get SQL-level analytics on your NoSQL MongoDB database.
Building Elasticsearch Queries using Knowi
This blog post provides a guide to building Elasticsearch queries. It also talks about some of Knowi’s key features/support for Elasticsearch queries.
MongoDB vs PostgreSQL: Choosing the Right Database For Your Needs [Updated 2026]
Choosing the right database is crucial for scaling modern applications. This in-depth comparison breaks down MongoDB vs. PostgreSQL across data models, performance, scalability, and real-world use cases—plus how you can query both using plain English with Knowi’s AI-powered analytics.
The Ultimate Sigma Review: Pros, Cons and who it is for.
Is Sigma the right BI tool for your team? Discover its pros, cons, and ideal use cases in this in-depth review.
The Ultimate Power BI Review for 2026: Strengths, Limitations, and Who It’s Right For
In this ultimate 2025 review, we break down who Power BI is right for, what it does best, and where it falls short—based on expert consensus and real-world use.
Best tool for ElasticSearch Analytics: Kibana vs Knowi vs Garfana
Explore top ElasticSearch reporting tools—Kibana, Knowi, and Grafana—and see how they compare on integration, analytics, ML, and real-time insights.
AI Agent Protocols Explained: What Are A2A and MCP and Why They Matter
A2A and MCP are AI Agent protocols key to building scalable AI agents, A2A enables agent communication, while MCP connects them to real-world tools and data systems.