Looker vs Microsoft SSRS

Overview

Looker

Stacks632

Followers656

Votes9

Microsoft SSRS

Stacks96

Followers138

Votes0

Looker vs Microsoft SSRS: What are the differences?

Introduction

Looker and Microsoft SSRS are both popular business intelligence tools used for data visualization and reporting. While they serve a similar purpose, there are key differences between the two that set them apart.

Deployment and Platform: Looker is a cloud-based platform that requires an internet connection to access, whereas Microsoft SSRS is an on-premises solution that requires installation on a server. Looker's cloud-based nature allows for quicker implementation and easier scalability, while SSRS provides more control over data and security as it is hosted on-premises.
Ease of Use and Learning Curve: Looker has a highly intuitive and user-friendly interface, making it easier for non-technical users to create their own reports and dashboards. SSRS, on the other hand, has a steeper learning curve and requires more technical knowledge to set up and use effectively.
Features and Flexibility: Looker offers a wide range of visualization options, interactive dashboards, and advanced analytics features such as data exploration and data discovery. It also has robust collaboration capabilities, allowing users to share and collaborate on reports easily. SSRS provides basic reporting capabilities with limited interactive features, making it less suitable for complex data analysis and exploration.
Integration and Compatibility: Looker can seamlessly integrate with a variety of data sources and tools, including popular databases, data warehouses, and cloud platforms. It also offers APIs for custom integrations. SSRS is mainly designed for Microsoft SQL Server, although it can also connect to other data sources with some configuration. It tightly integrates with other Microsoft tools such as Excel and SharePoint.
Scalability and Performance: Looker's cloud-based architecture allows for automatic scalability, ensuring that it can handle large volumes of data and users without performance degradation. SSRS's performance is dependent on the resources of the server it is installed on, making it less scalable and potentially slower for large datasets.
Pricing and Licensing: Looker follows a subscription-based pricing model, where users pay based on the number of users and the level of functionality required. SSRS is included as part of the SQL Server licensing, making it a cost-effective option for organizations already using the Microsoft ecosystem.

In summary, Looker is a cloud-based, user-friendly, and scalable BI tool with advanced analytics capabilities and flexible integration options, while Microsoft SSRS is an on-premises, more technical, and basic reporting tool tightly integrated with the Microsoft ecosystem.

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Advice on Looker, Microsoft SSRS

Vojtech

Head of Data at Mews

Nov 24, 2019

Decided

Power BI is really easy to start with. If you have just several Excel sheets or CSV files, or you build your first automated pipeline, it is actually quite intuitive to build your first reports.

And as we have kept growing, all the additional features and tools were just there within the Azure platform and/or Office 365.

Since we started building Mews, we have already passed several milestones in becoming start up, later also a scale up company and now getting ready to grow even further, and during all these phases Power BI was just the right tool for us.

353k views353k

Comments

Wei

CTO at Flux Work

Jan 8, 2020

Decided

Very easy-to-use UI. Good way to make data available inside the company for analysis.

Has some built-in visualizations and can be easily integrated with other JS visualization libraries such as D3.

Can be embedded into product to provide reporting functions.

Support team are helpful.

The only complain I have is lack of API support. Hard to track changes as codes and automate report deployment.

230k views230k

Comments

Detailed Comparison

Looker	Microsoft SSRS
We've built a unique data modeling language, connections to today's fastest analytical databases, and a service that you can deploy on any infrastructure, and explore on any device. Plus, we'll help you every step of the way.	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.
Zero-lag access to data;No limits;Personalized setup and support;No uploading, warehousing, or indexing;Deploy anywhere;Works in any browser, anywhere;Personalized access points	"Traditional" paginated reports; New mobile reports; A modern web portal
Statistics
Stacks 632	Stacks 96
Followers 656	Followers 138
Votes 9	Votes 0
Pros & Cons
Pros 4 Real time in app customer chat support 4 GitHub integration 1 Reduces the barrier of entry to utilizing data Cons 3 Price	No community feedback yet
Integrations
No integrations available	Microsoft SQL Server

What are some alternatives to Looker, 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.

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

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.

Related Comparisons

Looker vs Microsoft SSRS: What are the differences?

Introduction

Deployment and Platform: Looker is a cloud-based platform that requires an internet connection to access, whereas Microsoft SSRS is an on-premises solution that requires installation on a server. Looker's cloud-based nature allows for quicker implementation and easier scalability, while SSRS provides more control over data and security as it is hosted on-premises.
Ease of Use and Learning Curve: Looker has a highly intuitive and user-friendly interface, making it easier for non-technical users to create their own reports and dashboards. SSRS, on the other hand, has a steeper learning curve and requires more technical knowledge to set up and use effectively.
Features and Flexibility: Looker offers a wide range of visualization options, interactive dashboards, and advanced analytics features such as data exploration and data discovery. It also has robust collaboration capabilities, allowing users to share and collaborate on reports easily. SSRS provides basic reporting capabilities with limited interactive features, making it less suitable for complex data analysis and exploration.
Integration and Compatibility: Looker can seamlessly integrate with a variety of data sources and tools, including popular databases, data warehouses, and cloud platforms. It also offers APIs for custom integrations. SSRS is mainly designed for Microsoft SQL Server, although it can also connect to other data sources with some configuration. It tightly integrates with other Microsoft tools such as Excel and SharePoint.
Scalability and Performance: Looker's cloud-based architecture allows for automatic scalability, ensuring that it can handle large volumes of data and users without performance degradation. SSRS's performance is dependent on the resources of the server it is installed on, making it less scalable and potentially slower for large datasets.
Pricing and Licensing: Looker follows a subscription-based pricing model, where users pay based on the number of users and the level of functionality required. SSRS is included as part of the SQL Server licensing, making it a cost-effective option for organizations already using the Microsoft ecosystem.

Looker vs Microsoft SSRS

Overview

Looker vs Microsoft SSRS: What are the differences?