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Databricks vs Looker Studio comparison

 

Comparison Buyer's Guide

Executive Summary

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

Databricks
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
88
Ranking in other categories
Cloud Data Warehouse (7th), Data Science Platforms (1st), Streaming Analytics (1st)
Looker Studio
Average Rating
7.8
Reviews Sentiment
7.1
Number of Reviews
12
Ranking in other categories
Reporting (11th)
 

Mindshare comparison

While both are Business Intelligence solutions, they serve different purposes. Databricks is designed for Cloud Data Warehouse and holds a mindshare of 8.4%, up 3.2% compared to last year.
Looker Studio, on the other hand, focuses on Reporting, holds 2.5% mindshare, down 2.7% since last year.
Cloud Data Warehouse
Reporting
 

Featured Reviews

ShubhamSharma7 - PeerSpot reviewer
Capability to integrate diverse coding languages in a single notebook greatly enhances workflow
Databricks offers various courses that I can use, whether it's PySpark, Scala, or R. I can leverage all these courses in a single notebook, which is beneficial for clients as they can access various tools in one place whenever needed. This is quite significant. I usually work with PySpark based on client requirements. After coding, I feed the Databricks notebooks into the ADF pipeline for updates. Databricks' capability to process data in parallel enhances data processing speed. Furthermore, I can connect our Databricks notebook directly with Power BI and other visualization tools like Qlik. Once we develop code, it allows us to transform raw data into visualizations for clients using analysis diagrams, which is very helpful.
Srini-Dhanaraj - PeerSpot reviewer
Available for free and can help businesses resolve their data migration problems
It is a stable solution. Stability-wise, I rate the solution a ten out of ten. Google Data Studio is a cloud-based tool. With cloud-based tools, there can be two challenges, the first one being associated with the bandwidth of your data strength. If I run a report from my home because of the wi-fi connection, it may give an excellent response. When I run the reports, Google Data Studio develops reports from my home, and because of wi-fi, it works in an excellent manner. When I am on the road or at the wheel, if I use the internet data from my mobile to browse my reports, the performance may not be good, and this issue is not because of the product but because of the bandwidth. The second issue arises when you connect Google Data Studio to a source system to extract the data to do the visualization. If the source system is not responding as quickly as expected, it could be the reason why the report may be printed slowly. Considering the aforementioned aspects, the problem may not be because of Google Data Studio but because of the source system.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"I like the ability to use workspaces with other colleagues because you can work together even without seeing the other team's job."
"Databricks helps crunch petabytes of data in a very short period of time."
"Databricks' capability to process data in parallel enhances data processing speed."
"The solution is easy to use and has a quick start-up time due to being on the cloud."
"Databricks offers various courses that I can use, whether it's PySpark, Scala, or R."
"The most valuable features of the solution are the hardware and the resources it quickly provides without much hassle."
"The setup was straightforward."
"Databricks gives you the flexibility of using several programming languages independently or in combination to build models."
"The ability to design complex data models and equations."
"The ability to integrate with a great variety of data sources."
"Data Studio integrates seamlessly with other Google products, and we can use it with other APIs if we like."
"Valuable features include advanced integrated analysis and easy implementation."
"I am impressed with the tool's scheduling mechanism, refresh mechanism, and different types of charts."
"The best thing about the tool is that it allows you to share information easily and dashboards with colleagues and teammates because it's all online. No matter where you are, as long as you have the Internet, you can connect and use these dashboards. Google made good documentation for this tool. There are many examples of how to use and create dashboards and videos on YouTube. So, I think it's easy to learn."
"I find it favorable regarding speed of development, ease of building, and flexibility."
"The solution is free so that is a good feature."
 

Cons

"It would be great if Databricks could integrate all the cloud platforms."
"The product cannot be integrated with a popular coding IDE."
"Databricks is an analytics platform. It should offer more data science. It should have more features for data scientists to work with."
"I would like it if Databricks made it easier to set up a project."
"The solution could be improved by adding a feature that would make it more user-friendly for our team. The feature is simple, but it would be useful. Currently, our team is more familiar with the language R, but Databricks requires the use of Jupyter Notebooks which primarily supports Python. We have tried using RStudio, but it is not a fully integrated solution. To fully utilize Databricks, we have to use the Jupyter interface. One feature that would make it easier for our team to adopt the Jupyter interface would be the ability to select a specific variable or line of code and execute it within a cell. This feature is available in other Jupyter Notebooks outside of Databricks and in our own IDE, but it is not currently available within Databricks. If this feature were added, it would make the transition to using Databricks much smoother for our team."
"I have seen better user interfaces, so that is something that can be improved."
"The API deployment and model deployment are not easy on the Databricks side."
"I would like to see more documentation in terms of how an end-user could use it, and users like me can easily try it and implement use cases."
"It's not yet a replacement for a complete BI tool."
"Panels are not as easy to use as other data extraction UIs."
"The tool should come up with data modeling layer features that are present in other products like Power BI."
"The tool has a lot of room for improvement. It's not very professional and allows for only simple tasks like indicating KPIs or quick calculations. It lacks a good calculation-based language like Power BI's DAX, making it less suitable for professional use. Additionally, the variety of visualization tools is limited, and customization options are restricted."
"The challenges with Google Data Studio are associated with the security part, making it an area where improvements are required."
"The performance of Looker needs improvement, particularly the report loading time, which is critical for business users."
"The tool should improve on live data integration for quicker data reflection."
"Insisting on forums, blogs and community outreach in communications, and posting videos on an established calendar would be useful."
 

Pricing and Cost Advice

"The solution is affordable."
"Databricks is a very expensive solution. Pricing is an area that could definitely be improved. They could provide a lower end compute and probably reduce the price."
"The price is okay. It's competitive."
"I do not exactly know the costs, but one of our clients pays between $100 USD and $200 USD monthly."
"The solution is based on a licensing model."
"Databricks are not costly when compared with other solutions' prices."
"The product pricing is moderate."
"The solution uses a pay-per-use model with an annual subscription fee or package. Typically this solution is used on a cloud platform, such as Azure or AWS, but more people are choosing Azure because the price is more reasonable."
"The product is available for free."
"The solution is free but the Google Looker is expensive."
"I think the tool is cheap because you don't need to pay anything for using the tool. However, when connecting and analyzing other data sources, you should consider where to analyze this information because Google Data Studio doesn't handle much data well. You must also consider how you will connect this data to it. In this case, you might need to hire DevOps or a data team to help with these issues."
"The cost is quite affordable based on feature analysis."
"The tool is free."
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Top Industries

By visitors reading reviews
Financial Services Firm
17%
Computer Software Company
11%
Manufacturing Company
9%
Healthcare Company
6%
Computer Software Company
14%
Manufacturing Company
11%
Financial Services Firm
11%
Educational Organization
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

Which do you prefer - Databricks or Azure Machine Learning Studio?
Databricks gives you the option of working with several different languages, such as SQL, R, Scala, Apache Spark, or Python. It offers many different cluster choices and excellent integration with ...
How would you compare Databricks vs Amazon SageMaker?
We researched AWS SageMaker, but in the end, we chose Databricks. Databricks is a Unified Analytics Platform designed to accelerate innovation projects. It is based on Spark so it is very fast. It...
Which would you choose - Databricks or Azure Stream Analytics?
Databricks is an easy-to-set-up and versatile tool for data management, analysis, and business analytics. For analytics teams that have to interpret data to further the business goals of their orga...
What do you like most about Google Data Studio?
The company dashboard is useful because we could share it via a link as a reminder for everyone to check it weekly. We observed the progress of our portfolio from last week to the current week, all...
What needs improvement with Google Data Studio?
The tool should improve on live data integration for quicker data reflection. Currently, changes in Google Sheets take about three to five minutes to reflect in Looker Studio. Overall, the interfac...
What is your primary use case for Google Data Studio?
I use Looker Studio primarily for dashboard creation and data analytics. I have integrated it with Google Sheets, and I use it for project plan maintenance and data tracking.
 

Also Known As

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash
Data Studio
 

Overview

 

Sample Customers

Elsevier, MyFitnessPal, Sharethrough, Automatic Labs, Celtra, Radius Intelligence, Yesware
Genesys, Shueisha
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