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Knowi VS Ember-cli

Compare Knowi VS Ember-cli and see what are their differences

Knowi

Knowi is an agentic analytics platform. AI agents work inside the data layer to query SQL, NoSQL and APIs directly, join across sources without ETL, and build dashboards teams can use or embed in their own product.

Rating
0 reviews
Pricing
Free Free trial
Alternatives Is it good?
E
Ember-cli

Application and Data, Libraries, and JavaScript Framework Components

Rating
0 reviews
Alternatives Is it good?
HIVLY.APP
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Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Which is more popular?

Based on our record, Ember-cli seems to be more popular. It has been mentioned 1 time since March 2021.

social mentions
0 vs 1
Analytics popularity
100% vs 0%

Base details

Website, pricing, platforms and company facts side by side.

Knowi
E
Ember-cli
Website knowi.com cli.emberjs.com
Pricing
Free Free trial Official pricing
—
Company Startup from the United States · 20 - 49 employees · 2015 —
Listed in
Analytics Product Analytics IoT Platform Business Intelligence Embedded Analytics Data Visualization Reporting & Dashboard AI Agents Agentic Analytics Analytics Dashboard Marketing Analytics +8
Developer Tools Design Tools Productivity

About Knowi and Ember-cli

In their own words, as submitted to SaaSHub.

Knowi
E
Ember-cli

Knowi is the Agentic Analytics Platform. It unifies data from anywhere, adds a governed semantic layer, and deploys AI agents that analyze, monitor, and act on live business data. Traditional BI tools bolt AI onto dashboards. Knowi was built AI-first. The semantic layer defines your metrics,...

Read more about Knowi

No description of Ember-cli yet.

Features and specs

What each product offers, as listed by its team.

Knowi 10 features
E
Ember-cli 5 features
  • Agents Inside the Data Layer
    AI agents connect to schemas and the query engine directly rather than sitting on top of finished dashboards, so they build queries, widgets and dashboards instead of only answering questions about ones that already exist.
  • Native NoSQL Analytics
    Query MongoDB and Elasticsearch in their own query language, including nested documents and arrays, without a BI connector or a separate flattening step.
  • Cross-Source Joins Without ETL
    Blend MongoDB, PostgreSQL, Snowflake, Databricks SQL, Trino, Salesforce and REST APIs in a single query, without first moving the data into a warehouse.
  • Semantic Layer as a Dataset Service
    Curated datasets, governed business definitions and a shared glossary the data team controls, so plain-English questions resolve against approved metrics rather than raw tables.
  • Wide Range of Integrations
    The platform connects to relational databases, NoSQL stores, cloud warehouses, SaaS APIs and files, including MongoDB, Elasticsearch, PostgreSQL, MySQL, Snowflake, Databricks SQL, Trino, BigQuery, Redshift, Salesforce and REST endpoints.
  • Real-Time Insights
    Knowi provides real-time data processing and visualization, which enables businesses to access up-to-date insights for timely decision-making.
  • Alerts and Scheduled Reporting
    Threshold and anomaly alerts routed to Slack, email or webhooks, plus scheduled PDF and CSV delivery.
  • MCP Server for AI Assistants
    A Model Context Protocol server so assistants such as Claude can query data, build widgets and create dashboards through Knowi's governed layer.
  • Flexible Deployment
    Run on Knowi Cloud, inside your own VPC, or fully on-premise.
  • No-Code Data Analytics
    Knowi offers a no-code platform that allows users to perform data analytics tasks without needing in-depth programming skills, making it accessible to data-driven teams.
  • Convention over Configuration
    Ember-cli enforces strong conventions for file structure, naming, and project organization, which reduces decision fatigue and makes it easier for developers to jump between different Ember projects with minimal onboarding time.
  • Built-in Tooling
    Comes with a robust set of built-in tools including a development server, testing framework integration (QUnit), asset compilation, and live reload, reducing the need to manually configure and integrate third-party build tools.
  • Addon Ecosystem
    Ember-cli supports a rich ecosystem of addons that can be easily installed and integrated into projects, allowing developers to extend functionality without reinventing the wheel for common features.
  • Blueprints and Generators
    Provides powerful generator commands (blueprints) that scaffold components, routes, models, and other application pieces quickly, speeding up development and ensuring consistency across the codebase.
  • Stable Long-term Support
    Ember-cli follows Ember's release cycle with clear LTS (Long Term Support) versions, providing stability and predictability for teams maintaining large applications over time.

Possible disadvantages

  • Steep Learning Curve
    The strict conventions and unique architecture of Ember-cli can be difficult for newcomers to learn, especially those coming from more flexible frameworks or with no prior Ember experience.
  • Smaller Community Compared to Alternatives
    Compared to tools like Vite, Webpack, or CRA used with React/Vue, Ember-cli has a smaller community and ecosystem, which can mean fewer third-party resources, tutorials, and community-driven troubleshooting.
  • Build Performance
    For large applications, Ember-cli's build process can become slow, and while improvements have been made with embroider, some developers still report slower build times compared to more modern bundlers.
  • Rigid Structure
    The opinionated nature of Ember-cli, while helpful for consistency, can feel restrictive for developers who prefer more flexibility in structuring their applications or adopting non-standard patterns.
  • Migration Complexity
    Upgrading between major Ember-cli versions or migrating to newer build systems like Embroider can be complex and time-consuming, particularly for older or heavily customized applications.

Analysis

An editorial look at what each product does well and who it suits.

Knowi
E
Ember-cli

No analysis of Knowi yet.

Overall verdict

  • Ember CLI is a solid, mature command-line tool for building Ember.js applications, offering strong conventions, built-in tooling, and a stable development workflow that has been refined over many years.

Why this product is good

  • Provides a standardized project structure and conventions, reducing setup decisions and configuration overhead
  • Includes built-in support for ES modules, testing, and asset compilation out of the box
  • Strong addon ecosystem allows easy integration of third-party functionality
  • Backed by the official Ember.js team, ensuring long-term support and consistent updates
  • Automatic reloading and rebuilding during development speeds up the workflow
  • Encourages best practices like testing and modular code organization

Recommended for

  • Teams building large-scale, maintainable web applications with Ember.js
  • Developers who prefer convention-over-configuration frameworks
  • Projects that require long-term stability and structured upgrade paths
  • Organizations already invested in the Ember.js ecosystem
  • Developers who value built-in testing and tooling integration without extra setup

Videos

Walkthroughs and reviews on video.

Knowi 1 video + Add
E
Ember-cli 0 videos + Add

Knowi: End-to-End AI Analytics Platform - Architecture Overview

No Ember-cli videos yet. You could help us improve this page by suggesting one.

Category popularity

How often each product is chosen within a category, 0–100% relative to the other.

Score bands 0–20 21–40 41–50 51–60 61–100
Knowi
E
Ember-cli
100% 100%
Analytics
0% 0%
0% 0%
Productivity
100% 100%
100% 100%
IoT Platform
0% 0%
0% 0%
Developer Tools
100% 100%

Questions & Answers

As answered by people managing Knowi and Ember-cli.

Who are some of the biggest customers of your product?

Knowi's answer

Verizon Telstra Everbridge ConvergeOne NJM Insurance Volante Systems intlx Solutions Alteas Health Hometime Tata

What makes your product unique?

Knowi's answer

Knowi runs AI agents inside the data layer rather than on top of finished dashboards. The agents reach schemas and the query engine directly, which means they can build queries, widgets and dashboards, not just answer questions about ones that already exist.

That architecture comes from what Knowi was built to do: query data where it already lives. It speaks MongoDB and Elasticsearch in their own query language, including nested documents and arrays, and it joins across MongoDB, PostgreSQL, Snowflake, Databricks SQL, Trino, Salesforce and REST APIs in a single query without first moving anything into a warehouse.

Knowi also runs its own AI by default, with OpenAI and Claude available as optional integrations rather than requirements, and it deploys to cloud, your own VPC, on-premises via Docker or Kubernetes, or air-gapped.

Why should a person choose your product over its competitors?

Knowi's answer

Three practical reasons.

Your data does not have to be relational first. Most BI tools need a warehouse and an ETL pipeline before you see a chart, which means unstructured, nested and API data either gets flattened or gets left out. Knowi queries those sources natively, so the modelling work you would normally do up front becomes optional.

The AI is part of the query path, not a chat box on the side. Many platforms added a copilot that describes existing dashboards. Knowi's agents have access to the schema and the query engine, so they can create new datasets, widgets and dashboards from a question.

You control where it runs and which model touches your data. Knowi AI is the default, third-party models are optional, and deployment can be Knowi Cloud, your own VPC, on-premises, or air-gapped. Knowi is SOC 2 Type II certified, GDPR compliant, and offers a HIPAA BAA.

How would you describe the primary audience of your product?

Knowi's answer

Data, engineering and product teams at mid-market and enterprise companies whose data is spread across more than one kind of system: NoSQL alongside SQL, warehouses alongside SaaS APIs and documents.

Two buying patterns show up most often. Internal analytics teams who need governed self-service across sources without building a pipeline for every question. And product teams who need customer-facing, multi-tenant analytics embedded inside their own application with row-level access control.

By industry, the customer base skews to telecom, healthcare, manufacturing, SaaS and adtech, proptech and e-commerce. Knowi is sold through a sales team and priced per deployment rather than by public self-serve tier.

What's the story behind your product?

Knowi's answer

Knowi was founded in 2014, at the point where a lot of production data had stopped being relational. Teams were running MongoDB and Elasticsearch, and the BI tools of the day all assumed a star schema in a warehouse. Getting a dashboard meant building a pipeline first, and anything nested or semi-structured got flattened or dropped along the way.

Knowi was built the other way round: connect to the source, query it in its own language, and join across sources at query time instead of moving the data. Cross-source joins, post-query transformation and a dataset layer that data teams could govern followed from that starting point, and embedded analytics came from customers who wanted to give the same views to their own users.

The AI work is a continuation rather than a pivot. Because Knowi already owned the query path across every connected source, AI agents could be placed inside the data layer with access to schemas and the query engine, instead of being bolted onto a finished dashboard.

User comments

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Social recommendations and mentions

Recommendations tracked on public social media and blogs since March 2021.

Knowi 0 mentions
E
Ember-cli 1 mention

Tracking Knowi since Mar 2021.

  • Help! Why does chrome console inner text and my program inner text not return the same values? (spent nearly the whole day trying to extract an element). Turned to reddit as its always had the best community. Any help is MASSIVELY appreciated. Puppeteer!!
    The webpage is LinkedIn.com. While this isn’t a framework, I know that are using https://cli.emberjs.com/release/. Source: about 5 years ago

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