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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

"We like that this solution can handle a wide variety and velocity of data engineering, either in batch mode or real-time."
"Databricks is a unified solution that we can use for streaming. It is supporting open source languages, which are cloud-agnostic. When I do database coding if any other tool has a similar language pack to Excel or SQL, I can use the same knowledge, limiting the need to learn new things. It supports a lot of Python libraries where I can use some very easily."
"The ability to stream data and the windowing feature are valuable."
"It is fast, it's scalable, and it does the job it needs to do."
"This solution offers a lake house data concept that we have found exciting. We are able to have a large amount of data in a data lake and can manage all relational activities."
"The most valuable feature is the Spark cluster which is very fast for heavy loads, big data processing and Pi Spark."
"The initial setup is pretty easy."
"Easy to use and requires minimal coding and customizations."
"The product's initial setup phase is very simple."
"Valuable features include advanced integrated analysis and easy implementation."
"The solution is free so that is a good feature."
"Looker's ability to perform aggregation before visualization allows for effective data slicing and dicing."
"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, allowing us to compare revenues."
"I am impressed with the tool's scheduling mechanism, refresh mechanism, and different types of charts."
"The ability to integrate with a great variety of data sources."
"The integration with Excel and Google Sheets is a valuable feature, making it easy to access and visualize data."
 

Cons

"Costs can quickly add up if you don't plan for it."
"The tool should improve its integration with other products."
"The solution could improve by providing better automation capabilities. For example, working together with more of a DevOps approach, such as continuous integration."
"The connectivity with various BI tools could be improved, specifically the performance and real time integration."
"The Databricks cluster can be improved."
"Cluster failure is one of the biggest weaknesses I notice in our Databricks."
"I would like to see the integration between Databricks and MLflow improved. It is quite hard to train multiple models in parallel in the distributed fashions. You hit rate limits on the clients very fast."
"Pricing is one of the things that could be improved."
"When you physically install a product on one machine instead of the cloud, you have a better visibility, best icon quality, etc.. It's more of an issue with how we are adapting to the transition. We are still in the early moments of using this tool, and we need to go deeper to discover some improvements."
"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 tool should improve on live data integration for quicker data reflection."
"Other tools might be worth considering if you need more advanced features or support for a larger user base."
"Stability and scalability an be improved for a full ten."
"The performance of Looker needs improvement, particularly the report loading time, which is critical for business users."
"There is a significant degree of sophistication required to compete with Tableau or Cognos."
"The challenges with Google Data Studio are associated with the security part, making it an area where improvements are required."
 

Pricing and Cost Advice

"Price-wise, I would rate Databricks a three out of five."
"Whenever we want to find the actual costing, we have to send an email to Databricks, so having the information available on the internet would be helpful."
"The solution requires a subscription."
"I am based in South Africa, where it is expensive adapting to the cloud, and then there is the price for the tool itself."
"It is an expensive tool. The licensing model is a pay-as-you-go one."
"I would rate Databricks' pricing seven out of ten."
"Licensing on site I would counsel against, as on-site hardware issues tend to really delay and slow down delivery."
"Databricks are not costly when compared with other solutions' prices."
"The product is available for free."
"The solution is free but the Google Looker is expensive."
"The tool is free."
"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."
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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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