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Databricks vs Looker 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
Average Rating
8.0
Number of Reviews
19
Ranking in other categories
Embedded BI (5th)
 

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, on the other hand, focuses on Embedded BI, holds 9.3% mindshare, down 11.9% since last year.
Cloud Data Warehouse
Embedded BI
 

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.
Kishore Jhunjhunwala - PeerSpot reviewer
A cloud solution for operational reporting but is expensive
Some basic feature that is available in other reporting tools is missing. Looker has the ability to show more than 5,000 rows for operational reporting. Some reporting tools allow users to scroll down to see more than 5,000 rows, but in Looker, you have to download the entire dataset. Looker should consider adding a scroll-down option to allow users to view large datasets on screen without downloading them. Looker has some options for granting users access as viewers. However, viewers cannot download the entire dataset. Only superusers can download the whole dataset on the Explore screen. This is a big limitation, as you cannot give any user viewer access. You can give access to superuser access, which is a cost to the company.

Quotes from Members

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

Pros

"It can send out large data amounts."
"The ability to stream data and the windowing feature are valuable."
"It offers AI functionalities that assist with code management and machine learning processes."
"Its lightweight and fast processing are valuable."
"Databricks integrates well with other solutions."
"Databricks' capability to process data in parallel enhances data processing speed."
"I would rate them ten out of ten."
"The most valuable feature of Databricks is the notebook, data factory, and ease of use."
"I would rate the stability a ten out of ten. I didn't face any issues with stability."
"We can centralize all our data models."
"The product is easy to use."
"It's quite effortless to navigate through various applications and review their updated data in real-time."
"With Looker, I have experienced benefits in terms of usability and shareability."
"Looker allows you to generate the most optimal SQL queries in a DC through UI actions. We had signed a contract with Google Cloud to use BigQuery. That was the primary reason we adopted Looker. It works better with BigQuery than any other BI platform. We also like how this tool was developed. It was designed with an eye toward microservices architecture."
"From a developer's perspective, the way the functionality's being handled is great."
"It is a pretty stable solution because it is a cloud-based product."
 

Cons

"Would be helpful to have additional licensing options."
"There are no direct connectors — they are very limited."
"Databricks is not geared towards the end-user, but rather it is for data engineers or data scientists."
"It would be great if Databricks could integrate all the cloud platforms."
"The interface of Databricks could be easier to use when compared to other solutions. It is not easy for non-data scientists. The user interface is important before we had to write code manually and as solutions move to "No code AI" it is critical that the interface is very good."
"It should have more compatible and more advanced visualization and machine learning libraries."
"Generative AI is catching up in areas like data governance and enterprise flavor. Hence, these are places where Databricks has to be faster."
"The connectivity with various BI tools could be improved, specifically the performance and real time integration."
"The visualization capability of the product is limited."
"Integrations with other BI tools could be better."
"The product does not have documented material."
"Looker doesn't connect to Excel, which is a huge disappointment because a lot of data is presented in Excel. Also, it can't consume data directly from REST APIs, which is necessary. Looker needs to expand its horizons when it comes to data sources. The inability to connect to different data sources is hampering our use cases. Currently, it only has an ODBC connection that connects to a database. It needs to connect to other data sources, such as Excel, APIs, and different platforms."
"The main area of concern in Looker is probably related to blending the data from the different sources, including the data present internally in the company and on the cloud."
"The integration with different databases must be improved."
"Stability needs improvement."
"It needs to be more user-friendly."
 

Pricing and Cost Advice

"There are different versions."
"The product pricing is moderate."
"We're charged on what the data throughput is and also what the compute time is."
"We pay as we go, so there isn't a fixed price. It's charged by the unit. I don't have any details detail about how they measure this, but it should be a mix between processing and quantity of data handled. We run a simulation based on our use cases, which gives us an estimate. We've been monitoring this, and the costs have met our expectations."
"Databricks' cost could be improved."
"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 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."
"We only pay for the Azure compute behind the solution."
"I do not have to make any payments to use the solution."
"It is cheap."
"Looker is expensive and could be made better by reducing it."
"It's not cheap, but it's not expensive for big companies."
"The price of Looker usually depends on the solution's provider, but it is usually cheaper than the other products in the market. Looker is offered at different prices for different companies."
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Top Industries

By visitors reading reviews
Financial Services Firm
17%
Computer Software Company
11%
Manufacturing Company
9%
Healthcare Company
6%
Educational Organization
33%
Computer Software Company
10%
Financial Services Firm
10%
Manufacturing Company
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 Looker?
With Looker, I have experienced benefits in terms of usability and shareability.
What is your experience regarding pricing and costs for Looker?
I do not have to make any payments to use the solution. In the beginning, Looker may work fine for its users. If advanced users who have experience with BI tools use Looker, then they may find it t...
What needs improvement with Looker?
The visualization capability of the product is limited. From an improvement perspective, the product should have more visualization capability. I can't clean data in Looker, and if I try to do it, ...
 

Comparisons

 

Also Known As

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash
No data available
 

Overview

 

Sample Customers

Elsevier, MyFitnessPal, Sharethrough, Automatic Labs, Celtra, Radius Intelligence, Yesware
Yahoo!, Etsy, Kohler, Hipcamp, Hubspot, Kickstarter, Venmo, Dollar Shave Club, 600+ customer
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