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Databricks vs Treasure Data 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
91
Ranking in other categories
Cloud Data Warehouse (8th), Data Science Platforms (1st), Streaming Analytics (1st)
Treasure Data
Average Rating
9.0
Reviews Sentiment
5.8
Number of Reviews
1
Ranking in other categories
Data Warehouse (13th), Customer Data Platforms (CDP) (3rd)
 

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.
DEEPAK SINGH THAKUR - PeerSpot reviewer
Users can effortlessly create tables and manage data, even without utilizing the graphical interface
The initial setup is difficult due to the lack of detailed documentation. While the documentation provides a high-level overview, it lacks the specific instructions needed for setup. We relied on assistance from the Treasure Data team, including their support team, to navigate the process. Additionally, various policies to consider further complicate the setup, which ultimately requires time. We handle a large volume of data, and ensuring everything runs smoothly is crucial. Previously, it would take three to four months for one deployment due to the need to create workflows, conduct functional and comprehensive testing to ensure everything works seamlessly, and then proceed with delivery.
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Top Industries

By visitors reading reviews
Financial Services Firm
18%
Computer Software Company
10%
Manufacturing Company
9%
Healthcare Company
6%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

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 needs improvement with Treasure Data?
In data management, we have a lot of data, including some PII, visible to everyone without any restrictions. This poses a significant problem because there isn't proper control over who can access ...
What is your primary use case for Treasure Data?
We need to create a 360-degree profile of a user using data from multiple sources. Subsequently, we utilize this data for marketing purposes.
What advice do you have for others considering Treasure Data?
We used to gather data from various sources, including websites. The data used to flow in real-time, requiring us to capture it promptly. Within seconds, we could see four to five reports. Treasure...
 

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
Pioneer, Dentsu, Diverse, Albert, Retty, FreakOut, Mobfox, Pebble, Livesense, GREE, Cookpad, Dashbid, Cloud9, Just Premium
Find out what your peers are saying about Snowflake Computing, Microsoft, Google and others in Cloud Data Warehouse. Updated: June 2025.
860,592 professionals have used our research since 2012.