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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

"Having one solution for everything, from data engineering to machine learning, is beneficial since everything comes under one hood."
"The tool helps with data processing and analytics with large-scale data or big data since it is associated with managing data at a large scale."
"The most valuable feature is the ability to use SQL directly with Databricks."
"The solution is an impressive tool for data migration and integration."
"The solution is built from Spark and has integration with MLflow, which is important for our use case."
"The initial setup phase of Databricks was good."
"It helps integrate data science and machine learning capabilities."
"Databricks is a robust solution for big data processing, offering flexibility and powerful features."
"Data Studio integrates seamlessly with other Google products, and we can use it with other APIs if we like."
"The solution is free so that is a good feature."
"The ability to integrate with a great variety of data sources."
"Valuable features include advanced integrated analysis and easy implementation."
"I find it favorable regarding speed of development, ease of building, and flexibility."
"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."
"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."
 

Cons

"Databricks has added some alerts and query functionality into their SQL persona, but the whole SQL persona, which is like a role, needs a lot of development. The alerts are not very flexible, and the query interface itself is not as polished as the notebook interface that is used through the data science and machine learning persona. It is clunky at present."
"I have had some issues with some of the Spark clusters running on Databricks, where the Spark runtime and clusters go up and down, which is an area for improvement."
"The connectivity with various BI tools could be improved, specifically the performance and real time integration."
"The product could be improved regarding the delay when switching to higher-performing virtual machines compared to other platforms."
"The product could be improved by offering an expansion of their visualization capabilities, which currently assists in development in their notebook environment."
"Databricks' performance when serving the data to an analytics tool isn't as good as Snowflake's."
"Databricks requires writing code in Python or SQL, so if you're a good programmer then you can use Databricks."
"The product cannot be integrated with a popular coding IDE."
"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 should improve on live data integration for quicker data reflection."
"The performance of Looker needs improvement, particularly the report loading time, which is critical for business users."
"There are issues with integration and I encountered limits and warnings, especially with my pivot table size."
"Other tools might be worth considering if you need more advanced features or support for a larger user base."
"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."
"Panels are not as easy to use as other data extraction UIs."
 

Pricing and Cost Advice

"We find Databricks to be very expensive, although this improved when we found out how to shut it down at night."
"Licensing on site I would counsel against, as on-site hardware issues tend to really delay and slow down delivery."
"I do not exactly know the costs, but one of our clients pays between $100 USD and $200 USD monthly."
"There are different versions."
"Databricks uses a price-per-use model, where you can use as much compute as you need."
"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."
"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 price is okay. It's competitive."
"The product is available for free."
"The tool is free."
"The solution is free but the Google Looker is expensive."
"The cost is quite affordable based on feature analysis."
"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."
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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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