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  5. Microsoft SSRS vs Superset

Microsoft SSRS vs Superset

OverviewComparisonAlternatives

Overview

Superset
Superset
Stacks420
Followers1.0K
Votes45
Microsoft SSRS
Microsoft SSRS
Stacks96
Followers138
Votes0

Microsoft SSRS vs Superset: What are the differences?

Introduction

In this Markdown code, we will discuss the key differences between Microsoft SSRS (SQL Server Reporting Services) and Superset, which are both popular tools used for data visualization and reporting in the business intelligence domain.

  1. Deployment and Hosting Options: One key difference between Microsoft SSRS and Superset is the deployment and hosting options. Microsoft SSRS is typically installed on-premises and requires a dedicated server to host the reports. On the other hand, Superset is a web-based tool that can be deployed on a server and accessed through a web browser, making it more flexible for cloud-based deployments or running on a shared hosting environment.

  2. Data Sources and Connectivity: Microsoft SSRS primarily integrates with Microsoft SQL Server and other Microsoft data sources seamlessly. It provides native connectivity options, such as ODBC and OLE DB, to connect to various data sources. Superset, on the other hand, supports a wide range of data sources and connectors, including SQL databases, Druid, Hive, Impala, MongoDB, and more, making it more versatile when working with diverse data sources.

  3. Visualization Capabilities: Another significant difference lies in the visualization capabilities offered by these tools. Microsoft SSRS has a limited set of pre-built visualization options, including basic charts, tables, and matrices. While it is possible to extend the visualizations using custom code, it requires additional development effort. In contrast, Superset provides an extensive collection of visualizations out-of-the-box, including interactive charts, maps, Sankey diagrams, and more, empowering users with a broader range of options for data exploration and analysis.

  4. Collaboration and Sharing: Microsoft SSRS has built-in features for collaboration and sharing, enabling users to create subscriptions, schedule report delivery via email, and manage permissions for different users or user groups. With Superset, collaboration and sharing are built-in within the tool, allowing multiple users to work on the same dashboard concurrently, share insights through interactive dashboards, and even embed them in external websites or applications effortlessly.

  5. Customization and Extensibility: Microsoft SSRS offers a powerful report development environment with advanced customization capabilities through the use of expressions, parameters, and formatting options. It also provides the ability to embed custom code, enabling developers to create complex reports. Superset is designed to be highly customizable, allowing users to create custom visualizations using Python or JavaScript, define custom SQL queries, and modify the look and feel of the dashboards using CSS.

  6. Licensing and Cost: Microsoft SSRS is a part of the Microsoft SQL Server suite and typically requires the appropriate SQL Server license. It is offered in multiple editions, each varying in features and licenses. On the other hand, Superset is an open-source tool released under the Apache license, making it free to download, use, and modify. However, it is important to consider the associated costs of hosting and maintaining the Superset infrastructure.

In Summary, Microsoft SSRS and Superset differ in deployment options, data source connectivity, visualization capabilities, collaboration and sharing features, customization options, and licensing models.

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Detailed Comparison

Superset
Superset
Microsoft SSRS
Microsoft SSRS

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.

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.

A rich set of visualizations to analyze your data, as well as a flexible way to extend the capabilities;An extensible, high granularity security model allowing intricate rules on who can access which features, and integration with major authentication providers (database, OpenID, LDAP, OAuth & REMOTE_USER through Flask AppBuiler);A simple semantic layer, allowing to control how data sources are displayed in the UI, by defining which fields should show up in which dropdown and which aggregation and function (metrics) are made available to the user;Deep integration with Druid allows for Caravel to stay blazing fast while slicing and dicing large, realtime datasets;
"Traditional" paginated reports; New mobile reports; A modern web portal
Statistics
Stacks
420
Stacks
96
Followers
1.0K
Followers
138
Votes
45
Votes
0
Pros & Cons
Pros
  • 13
    Awesome interactive filtering
  • 9
    Free
  • 6
    Wide SQL database support
  • 6
    Shareable & editable dashboards
  • 5
    Great for data collaborating on data exploration
Cons
  • 4
    Link diff db together "Data Modeling "
  • 3
    It is difficult to install on the server
  • 3
    Ugly GUI
No community feedback yet
Integrations
No integrations available
Microsoft SQL Server
Microsoft SQL Server

What are some alternatives to Superset, Microsoft SSRS?

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.

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.

Periscope

Periscope

Periscope is a data analysis tool that uses pre-emptive in-memory caching and statistical sampling to run data analyses really, really fast.

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