Microsoft SSRS vs Redash

Overview

Redash

Stacks338

Followers502

Votes12

Microsoft SSRS

Stacks96

Followers138

Votes0

Microsoft SSRS vs Redash: What are the differences?

What is Microsoft SSRS? *A server-based report generating software system *. It provides a set of on-premises tools and services that create, deploy, and manage mobile and paginated reports.

What is Redash? Easily query an existing database, share the dataset and visualize it in different ways. 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.

Microsoft SSRS and Redash can be categorized as "Business Intelligence" tools.

Redash is an open source tool with 13.4K GitHub stars and 2.23K GitHub forks. Here's a link to Redash's open source repository on GitHub.

Sentry, Implisit, and Dyno are some of the popular companies that use Redash, whereas Microsoft SSRS is used by Ayuda, NeoQuant, and Business Logic. Redash has a broader approval, being mentioned in 49 company stacks & 54 developers stacks; compared to Microsoft SSRS, which is listed in 4 company stacks and 10 developer stacks.

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CLI (Node.js)

Manual

Detailed Comparison

Redash	Microsoft SSRS
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.	It provides a set of on-premises tools and services that create, deploy, and manage mobile and paginated reports. It delivers the right information to the right users.
Query Editor;Dashboards/Visualizations;Alerts;API;Support for querying multiple databases	"Traditional" paginated reports; New mobile reports; A modern web portal
Statistics
Stacks 338	Stacks 96
Followers 502	Followers 138
Votes 12	Votes 0
Pros & Cons
Pros 9 Open Source 3 SQL Friendly Cons 1 All results are loaded into RAM before displaying 1 Memory Leaks	No community feedback yet
Integrations
PostgreSQL Cassandra MongoDB Amazon DynamoDB Amazon RDS Amazon Athena Jira PagerDuty Prometheus Slack	Microsoft SQL Server

What are some alternatives to Redash, Microsoft SSRS?

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'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: 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

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

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

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

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.

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.