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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

"It offers AI functionalities that assist with code management and machine learning processes."
"It is fast, it's scalable, and it does the job it needs to do."
"When we have a huge volume of data that we want to process with speed, velocity, and volume, we go through Databricks."
"Databricks is hosted on the cloud. It is very easy to collaborate with other team members who are working on it. It is production-ready code, and scheduling the jobs is easy."
"The solution is very simple and stable."
"Imageflow is a visual tool that helps make it easier for business people to understand complex workflows."
"Databricks is based on a Spark cluster and it is fast. Performance-wise, it is great."
"Ability to work collaboratively without having to worry about the infrastructure."
"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 ability to design complex data models and equations."
"The ability to integrate with a great variety of data sources."
"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."
"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."
 

Cons

"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."
"If I want to create a Databricks account, I need to have a prior cloud account such as an AWS account or an Azure account. Only then can I create a Databricks account on the cloud. However, if they can make it so that I can still try Databricks even if I don't have a cloud account on AWS and Azure, it would be great. That is, it would be nice if it were possible to create a pseudo account and be provided with a free trial. It is very essential to creating a workforce on Databricks. For example, students or corporate staff can then explore and learn Databricks."
"It would be nice to have more guidance on integrations with ETLs and other data quality tools."
"The query plan is not easy with Databrick's job level. If I want to tune any of the code, it is not easily available in the blogs as well."
"Overall it's a good product, however, it doesn't do well against any individual best-of-breed products."
"Anyone who doesn't know SQL may find the product difficult to work with."
"The connectivity with various BI tools could be improved, specifically the performance and real time integration."
"We often use a single cluster to ingest Databricks, which Databricks doesn't recommend. They suggest using a no-cluster solution like job clusters. This can be overwhelming for us because we started smaller."
"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."
"Insisting on forums, blogs and community outreach in communications, and posting videos on an established calendar would be useful."
"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."
"There are issues with integration and I encountered limits and warnings, especially with my pivot table size."
"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."
"There is a significant degree of sophistication required to compete with Tableau or Cognos."
 

Pricing and Cost Advice

"The billing of Databricks can be difficult and should improve."
"I am based in South Africa, where it is expensive adapting to the cloud, and then there is the price for the tool itself."
"The solution is a good value for batch processing and huge workloads."
"Price-wise, I would rate Databricks a three out of five."
"Databricks uses a price-per-use model, where you can use as much compute as you need."
"The price of Databricks is reasonable compared to other solutions."
"My smallest project is around a hundred euros, and my most expensive is just under a thousand euros a week. That is based on terabytes of data processed each month."
"The cost for Databricks depends on the use case. I work on it as a consultant, so I'm using the client's Databricks, so it depends on how big the client is."
"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."
"The product is available for free."
"The solution is free but the Google Looker is expensive."
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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
12%
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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