Overview

Looker

Stacks632

Followers656

Votes9

Sisense

Stacks50

Followers66

Votes0

Looker vs Sisense: What are the differences?

## Key Differences Between Looker and Sisense

<Introduction>

1. **Pricing Model**: Looker offers a pricing model based on user licenses, while Sisense has a pricing model based on the amount of data processed. This means that Looker may be more cost-effective for organizations with a smaller number of users.
2. **User Interface**: Looker has a user-friendly interface with drag-and-drop functionalities and customizable dashboards, while Sisense provides a more robust interface with advanced visualization options and interactive features.
3. **Data Processing Speed**: Sisense boasts faster data processing speeds, especially with large datasets, compared to Looker. This can be critical for organizations requiring real-time insights from their data.
4. **Integration Capabilities**: Looker excels in its integration capabilities with various data sources and platforms, offering seamless connectivity for businesses with diverse data ecosystems. Sisense, on the other hand, may have limitations in terms of integration options.
5. **Scalability**: Sisense is known for its scalability, being able to handle large volumes of data and users without compromising performance. Looker may face challenges in scaling to accommodate growing data needs and user numbers.
6. **Support and Maintenance**: Looker provides extensive support services, including training resources and a dedicated customer success team, while Sisense might have a more limited support offering, potentially impacting the overall user experience.

In Summary, Looker and Sisense vary in their pricing models, user interfaces, data processing speeds, integration capabilities, scalability, and support services, catering to different needs and preferences in the realm of data analytics and business intelligence.

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Advice on Looker, Sisense

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	Sisense
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 is making business intelligence (BI) analytics easy with its simple drag-and-drop and scalable end-to-end BI processes that help to prepare, analyze, and visualize multiple complex datasets quickly.
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	Complex business queries without programming or SQL writing; Removes limitations to data size; Intuitive 'script-less' user interface; Consolidates, stores and accumulates data; Data mash-ups; Can be set up and used entirely in-house; Handles data at scale on a single commodity server.
Statistics
Stacks 632	Stacks 50
Followers 656	Followers 66
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	AtScale Vertica Dremio DataRobot Trifacta SAP HANA

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