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Reviews from AWS customer

6 AWS reviews

External reviews

637 reviews
from and

External reviews are not included in the AWS star rating for the product.


4-star reviews ( Show all reviews )

    Bruno A.

All in one Platform

  • June 28, 2022
  • Review provided by G2

What do you like best about the product?
Integration and flebility on the daily base speed up the development and delivery. Data lake and data sharing is amazing and away from the competitors in the market.
What do you dislike about the product?
It should be ease to get improvements in the platform and embedded reports for daily basis usage.
What problems is the product solving and how is that benefiting you?
Nothing


    Marcelo A.

Databricks

  • June 27, 2022
  • Review provided by G2

What do you like best about the product?
Really helpful abstractions, intuitive UI and attentive support.
What do you dislike about the product?
Very hermetic environment. Could allow more integrations with outer platforms.
What problems is the product solving and how is that benefiting you?
It really facilitates the construction and testing of daily workloads.


    Venkatraman S.

Changes due to Lakehouse usage

  • June 27, 2022
  • Review provided by G2

What do you like best about the product?
Databricks Data Science and Engineering Workspace allows writing the coding in various languages and it enables the ingestion process simpler and guarantee that data available for business queries are reliable and current
What do you dislike about the product?
Reusing the Cluster feature and delta live tables features was the least liked process, due to the missing link to the GIT integration directly from the Repos.

If this is available then we will be able to use these cool features widely
What problems is the product solving and how is that benefiting you?
Databricks Lakehouse platform has been used to resolve the common Big Data and the AI problems and helped our organization to utilize the cool compute features of Databricks


    Management Consulting

Databricks Rocks!

  • June 27, 2022
  • Review provided by G2

What do you like best about the product?
combines data warehousing with data lakes; ease of use and implementation; compatibility with BI tools
What do you dislike about the product?
nothing i can think of - databricks is awesome
What problems is the product solving and how is that benefiting you?
it helps with business intelligence and analytics and is easily used with our techstack


    Abel S.

Great platform for collaboration and data analysis

  • June 26, 2022
  • Review provided by G2

What do you like best about the product?
Integration with Github repos and CI/CD pipelines. Also having different ways to collaborate with team members and stakeholders (repos, workspace, Databricks SQL)
What do you dislike about the product?
Depending on cluster settings and number of users running queries at the same time and the number of jobs running at the same time, it can sometimes take time to run queries
What problems is the product solving and how is that benefiting you?
Having a single place to store data and being able to merge it and analyze it together is useful to enable insights for the decision-making roles as well as operations teams


    Dr. Ernie P.

The best platform for building the future

  • May 03, 2022
  • Review provided by G2

What do you like best about the product?
1. The core storage technology is Open Source (Delta Lake)
2. Multiple data formats fully accessible via Spark/Python or SQL
3. Ability to manage code via our own GitHub repositories
What do you dislike about the product?
1. Not always obvious which pieces are (or will be) open source vs proprietary
2. GitHub integration doesn't support multiple branches, making it difficult to develop alongside production
3. Hard mode-switch between SQL and Data Science user interfaces feels needlessly complex (though I understand there is some technical justification for it)
What problems is the product solving and how is that benefiting you?
1. THE single source of truth for all our enterprise data, including Salesforce and NetSuite
2. Straightforward integration of our business data with our IoT product data
3. Elegant console (using Quilt Data Smart Reports) for presenting that data to multiple stakeholders
Recommendations to others considering the product:
Decide up front how much you want to take advantage of their proprietary technology (such as live tables), versus industry standards such as Spark, SQL, and dbt. There's no right answer, but the more mindful you are about those tradeoffs the fewer regrets you will have down the road.


    Rahul N.

Going in the right direction but might take a while. Best platform to bet on

  • March 27, 2022
  • Review provided by G2

What do you like best about the product?
Easy to use and and very small learning curve. This makes it easy to start focusing on the actual probelm statement and start getting value out of it.
What do you dislike about the product?
UX. Though there are features available, sometime it's hard to find. If you're not trained, your eye might not catch it. Some features can only be applied via API. This require to keep a constant watch in the documentation to know what other options available. At least those options could be provided as a note in the UI for knowing there are other possibilities.
What problems is the product solving and how is that benefiting you?
We are building a data platform using lakehouse to empower the whole organisation to take data driven decision. Databricks providing us a platform to move fast without thinking much about infrastructure. We could easily scale. At the same time it is almost like open source. There is very little vendor lock-in risk.
Recommendations to others considering the product:
Use it to move fast! It cost a bit on the higher side. As it is built on top of open source, there are plenty of options to move out at a later point when you're mature if you are worried too much about the cost or just continue using it if you don't want the management overhead and the addon performance benifits.


    Financial Services

Lakehouse made simple

  • March 06, 2022
  • Review provided by G2

What do you like best about the product?
For me, I like the data science and SQL platform best. They are extremely helpful for my job, allowing me to streamline my work and automate it using Jobs.
What do you dislike about the product?
Sometimes the platform can be a bit slow to react but I'm not sure if it's the cluster size or something is wrong with Databricks itself. Overall I didn't find many issues with the platform.
What problems is the product solving and how is that benefiting you?
I'm solving automation issues along with ETL work. I'm able to use Databricks with our datalake in the easiest possible way, using different data formats with ease.


    Banking

Lakehouse brings the best of the data warehousing and data lake worlds under one solution

  • March 01, 2022
  • Review provided by G2

What do you like best about the product?
The slowly changing dimension features that comes out of the box with the lakehouse
What do you dislike about the product?
Lake of UI/UX to have a moth user experience
What problems is the product solving and how is that benefiting you?
It solves a lot of the standard engineering challenges when it comes to ingestion of data, data lineage and access management


    Marketing and Advertising

Amazing product which answers data people's persona

  • February 28, 2022
  • Review provided by G2

What do you like best about the product?
How a steep learning curve Databricks is, I'm enjoying learning all the time with such great materials and people.
What do you dislike about the product?
Sometimes I feel documentation is a bit misleading. E.g. Pandas UDF + ML model combined - the functionality of both is amazing, but actually it's not clear how to use it.
What problems is the product solving and how is that benefiting you?
I never understood the motivation of having lakehouse instead of bunch of parquets, plus not sure what happens behind the scenes. Whenever implementing a new product, one must know how and why to do it :)