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  5. Blazer vs Knowage

Blazer vs Knowage

OverviewComparisonAlternatives

Overview

Blazer
Blazer
Stacks23
Followers24
Votes0
GitHub Stars4.7K
Forks486
Knowage
Knowage
Stacks4
Followers15
Votes0
GitHub Stars430
Forks231

Blazer vs Knowage: What are the differences?

Introduction

Blazer and Knowage are two powerful tools used for data analysis and visualization in the world of business intelligence. Understanding the key differences between Blazer and Knowage is crucial for choosing the right tool for your specific needs.

1. Licensing: Blazer is an open-source project released under the MIT License, making it freely available for anyone to use, modify, or distribute. On the other hand, Knowage is a commercial product offered by Engineering Group, and it requires a subscription or license fee to access its full range of features.

2. Data Sources: Blazer primarily works with SQL databases, allowing users to connect directly to databases such as PostgreSQL, MySQL, and SQL Server. Knowage, on the other hand, supports a wider range of data sources, including NoSQL databases, OLAP cubes, and flat files, providing more flexibility in data connectivity.

3. User Interface: Blazer provides a simple and clean user interface, focusing on ease of use and quick data visualization. In contrast, Knowage offers a more comprehensive and customizable user interface, with a range of features for advanced data analysis, reporting, and dashboard creation.

4. Community Support: Blazer has a large and active community of developers and users who contribute to its ongoing development and provide support through forums, documentation, and tutorials. Knowage also has a community of users, but with a smaller presence compared to Blazer, potentially resulting in longer response times for troubleshooting and assistance.

5. Extensibility: Blazer offers limited extensibility through custom plugins and extensions, allowing users to enhance its functionality to some extent. Knowage, on the other hand, provides a robust framework for developing custom modules, connectors, and data sources, offering greater flexibility for tailoring the platform to specific business requirements.

6. Deployment Options: Blazer is typically deployed as a standalone application or integrated into existing web applications, providing a lightweight solution for data visualization. In comparison, Knowage offers on-premise, cloud, and hybrid deployment options, catering to organizations with diverse infrastructure needs.

In Summary, understanding the key differences between Blazer and Knowage in terms of licensing, data sources, user interface, community support, extensibility, and deployment options is essential for selecting the right business intelligence tool for your organization.

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Detailed Comparison

Blazer
Blazer
Knowage
Knowage

Share data effortlessly with your team

It is composed of several modules, each one conceived for a specific analytical domain. They can be used individually or combined with one another to ensure full coverage of user’ requirements, allowing to build a tailored product.

Secure - works with your authentication system;Variables - run the same queries with different values;Linked Columns - link to other pages in your apps or around the web;Smart Columns - get the data you want without all the joins;Smart Variables - no need to remember ids;Charts - visualize the data;Audits - all queries are tracked
Big Data; Smart Intelligence; Enterprise Reporting; Location Intelligence; Performance Management; Predictive Analysis; Embedded Intelligence
Statistics
GitHub Stars
4.7K
GitHub Stars
430
GitHub Forks
486
GitHub Forks
231
Stacks
23
Stacks
4
Followers
24
Followers
15
Votes
0
Votes
0
Integrations
PostgreSQL
PostgreSQL
MySQL
MySQL
Apache Spark
Apache Spark

What are some alternatives to Blazer, Knowage?

Metabase

Metabase

It is an easy way to generate charts and dashboards, ask simple ad hoc queries without using SQL, and see detailed information about rows in your Database. You can set it up in under 5 minutes, and then give yourself and others a place to ask simple questions and understand the data your application is generating.

Superset

Superset

Superset's main goal is to make it easy to slice, dice and visualize data. It empowers users to perform analytics at the speed of thought.

Cube

Cube

Cube: the universal semantic layer that makes it easy to connect BI silos, embed analytics, and power your data apps and AI with context.

Power BI

Power BI

It aims to provide interactive visualizations and business intelligence capabilities with an interface simple enough for end users to create their own reports and dashboards.

Mode

Mode

Created by analysts, for analysts, Mode is a SQL-based analytics tool that connects directly to your database. Mode is designed to alleviate the bottlenecks in today's analytical workflow and drive collaboration around data projects.

Google Datastudio

Google Datastudio

It lets you create reports and data visualizations. Data Sources are reusable components that connect a report to your data, such as Google Analytics, Google Sheets, Google AdWords and so forth. You can unlock the power of your data with interactive dashboards and engaging reports that inspire smarter business decisions.

AskNed

AskNed

AskNed is an analytics platform where enterprise users can get answers from their data by simply typing questions in plain English.

Shiny

Shiny

It is an open source R package that provides an elegant and powerful web framework for building web applications using R. It helps you turn your analyses into interactive web applications without requiring HTML, CSS, or JavaScript knowledge.

Redash

Redash

Redash helps you make sense of your data. Connect and query your data sources, build dashboards to visualize data and share them with your company.

Azure Synapse

Azure Synapse

It is an analytics service that brings together enterprise data warehousing and Big Data analytics. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources—at scale. It brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate BI and machine learning needs.

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