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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
89
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 8.8%, up 3.7% compared to last year.
Looker Studio, on the other hand, focuses on Reporting, holds 2.7% mindshare, up 2.6% 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

"The most valuable features of the solution are the hardware and the resources it quickly provides without much hassle."
"The initial setup is pretty easy."
"The most valuable feature is the ability to use SQL directly with Databricks."
"When we have a huge volume of data that we want to process with speed, velocity, and volume, we go through Databricks."
"The setup is quite easy."
"I work in the data science field and I found Databricks to be very useful."
"It helps integrate data science and machine learning capabilities."
"The integration with Python and the notebooks really helps."
"This has improved our organization by allowing people to see their data and develop visualizations themselves."
"Valuable features include advanced integrated analysis and easy implementation."
"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."
"The product's initial setup phase is very simple."
"Data Studio integrates seamlessly with other Google products, and we can use it with other APIs if we like."
"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."
"The ability to integrate with a great variety of data sources."
"I am impressed with the tool's scheduling mechanism, refresh mechanism, and different types of charts."
 

Cons

"I'm not the guy that I'm working with Databricks on a daily basis. I'm on the management team. However, my team tells me there are limitations with streaming events. The connectors work with a small set of platforms. For example, we can work with Kafka, but if we want to move to an event-driven solution from AWS, we cannot do it. We cannot connect to all the streaming analytics platforms, so we are limited in choosing the best one."
"When I used the support, I had communication problems because of the language barrier with the agent. The accent was difficult to understand."
"Instead of relying on a massive instance, the solution should offer micro partition levels. They're working on it, however, they need to implement it to help the solution run more effectively."
"The product could be improved regarding the delay when switching to higher-performing virtual machines compared to other platforms."
"I have seen better user interfaces, so that is something that can be improved."
"I would like it if Databricks adopted an interface more like R Studio. When I create a data frame or a table, R Studio provides a preview of the data. In R Studio, I can see that it created a table with so many columns or rows. Then I can click on it and open a preview of that data."
"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."
"One area of improvement is the Databricks File System (DBFS), where command-line challenges arise when accessing files. Standardization of file paths on the system could help, as engineers sometimes struggle."
"The tool should come up with data modeling layer features that are present in other products like Power BI."
"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."
"Insisting on forums, blogs and community outreach in communications, and posting videos on an established calendar would be useful."
"Panels are not as easy to use as other data extraction UIs."
"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."
"Stability and scalability an be improved for a full ten."
"There is a significant degree of sophistication required to compete with Tableau or Cognos."
"The performance of Looker needs improvement, particularly the report loading time, which is critical for business users."
 

Pricing and Cost Advice

"I rate the price of Databricks as eight out of ten."
"I would rate the tool’s pricing an eight out of ten."
"The pricing depends on the usage itself."
"Licensing on site I would counsel against, as on-site hardware issues tend to really delay and slow down delivery."
"There are different versions."
"The solution requires a subscription."
"The billing of Databricks can be difficult and should improve."
"The solution is based on a licensing model."
"The cost is quite affordable based on feature analysis."
"The tool is 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 product is available for free."
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Top Industries

By visitors reading reviews
Financial Services Firm
18%
Computer Software Company
10%
Manufacturing Company
9%
Healthcare Company
6%
Computer Software Company
14%
Financial Services Firm
13%
Manufacturing Company
10%
Educational Organization
7%
 

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.
 

Comparisons

 

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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