Amazon SageMaker vs Databricks Lakehouse Platform

Likelihood to Recommend

Amazon SageMaker is a great tool for developing machine learning models that take more effort than just point-and-click type of analyses. The software works well with the other tools in the Amazon ecosystem, so if you use Amazon Web Services or are thinking about it, SageMaker would be a great addition. SageMaker is great for consumer insights, predictive analytics, and looking for gems of insight in the massive amounts of data we create. SageMaker is less suitable for analysts who do generally "small" data analyses, and "small" data analyses in today's world can be billions of records.

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Thomas Young

Owner, previous CEO

Econometric StudiosFinancial Services, 11-50 employees

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If you need a managed big data megastore, which has native integration with highly optimized Apache Spark Engine and native integration with MLflow, go for Databricks Lakehouse Platform. The Databricks Lakehouse Platform is a breeze to use and analytics capabilities are supported out of the box. You will find it a bit difficult to manage code in notebooks but you will get used to it soon.

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Verified User

Engineer in Engineering

Computer Software Company, 1001-5000 employees

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Pros

Provides enough freedom for experienced data scientists and also for those who just need things done without going much deeper into building models.
Customization and easy to alter and change.
If you already are an Amazon user, you do not need to transition over to another software.

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Verified User

Employee in Human Resources

Real Estate Company, 1001-5000 employees

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Process raw data in One Lake (S3) env to relational tables and views
Share notebooks with our business analysts so that they can use the queries and generate value out of the data
Try out PySpark and Spark SQL queries on raw data before using them in our Spark jobs
Modern day ETL operations made easy using Databricks. Provide access mechanism for different set of customers

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Verified User

Team Lead in Engineering

Financial Services Company, 10,001+ employees

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Cons

The UI can be eased up a bit for use by business analysts and non technical users
For huge amount of data pull from legacy solutions, the platform lags a bit
Considering ML is an emerging topic and would be used by most of the organizations in future, the pipeline integrations can be optimized

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Verified User

Consultant in Marketing

Marketing & Advertising Company, 201-500 employees

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Better Localized Testing
When they were primarily OSS Spark; it was easier to test/manage releases versus the newer DB Runtime. Wish there was more configuration in Runtime less pick a version.
Graphing Support went non-existent; when it was one of their compelling general engine.

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Verified User

Director in Information Technology

Financial Services Company, 201-500 employees

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Pricing Details

General

Free Trial

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Free/Freemium Version

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Premium Consulting/Integration Services

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Entry-level set up fee?

No

Starting Price

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Amazon SageMaker Editions & Modules

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Additional Pricing Details

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General

Free Trial

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Free/Freemium Version

—

Premium Consulting/Integration Services

—

Entry-level set up fee?

No

Starting Price

$0.07 Per DBU

Databricks Lakehouse Platform Editions & Modules

Edition

Standard	$0.07¹
Premium	$0.10¹
Enterprise	$0.13¹

Per DBU

Additional Pricing Details

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Usability

No score

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Databricks Lakehouse Platform 9.0

Based on 3 answers

Because it is an amazing platform for designing experiments and delivering a deep dive analysis that requires execution of highly complex queries, as well as it allows to share the information and insights across the company with their shared workspaces, while keeping it secured.

in terms of graph generation and interaction it could improve their UI and UX

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Verified User

Manager in Product Management

Financial Services Company, 201-500 employees

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Support Rating

No score

No answers yet

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Databricks Lakehouse Platform 7.5

Based on 2 answers

One of the best customer and technology support that I have ever experienced in my career. You pay for what you get and you get the Rolls Royce. It reminds me of the customer support of SAS in the 2000s when the tools were reaching some limits and their engineer wanted to know more about what we were doing, long before "data science" was even a name. Databricks truly embraces the partnership with their customer and help them on any given challenge.

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Jonatan Bouchard

Director Data Science

CNTransportation/Trucking/Railroad, 10,001+ employees

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Alternatives Considered

Amazon SageMaker comes with other supportive services like S3, SQS, and a vast variety of servers on EC2. It's very comfortable to manage the process and also support the end application by one click hosting option. Also, it charges on the base of what you use and how long you use it, so it becomes less costly compared to others.

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Verified User

Employee in Research & Development

Computer Software Company, 501-1000 employees

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Databricks has a much better edge than Synapse in hundred different ways. Databricks has Photon engine, faster available release in cloud and databricks does not run on Open source spark version so better optimization, better performance and better agility and all kind of performance boost can be achieved in Databricks rather Open source synapse spark

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Verified User

Director in Information Technology

Hospitality Company, 10,001+ employees

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Contract Terms and Pricing Model

No score

No answers yet

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Databricks Lakehouse Platform 8.0

Based on 1 answer

The problem with this tool and all other ones that are at the top of the industry, it's so expensive that soon as another one will be on the market and deliver the same or different value, it will be catastrophic for them. So you get the fact that they are cashing every dime right now like SAS or Hadoop once did. Now, look at them

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Jonatan Bouchard

Director Data Science

CNTransportation/Trucking/Railroad, 10,001+ employees

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Professional Services

No score

No answers yet

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Databricks Lakehouse Platform 10.0

Based on 1 answer

Again, another level of professional services, this is not their biggest strength but this is the cherry on top. I couldn't think about any other professional services like this one. Now I'm talking about meaningful services that really help out our project and delivery.

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Jonatan Bouchard

Director Data Science

CNTransportation/Trucking/Railroad, 10,001+ employees

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Return on Investment

We have been able to deliver data products more rapidly because we spend less time building data pipelines and model servers.
We can prototype more rapidly because it is easy to configure notebooks to access AWS resources.
For our use-cases, serving models is less expensive with SageMaker than bespoke servers.

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Gavin Hackeling

Data Scientist

Wonder (AskWonder.com)Research, 11-50 employees

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Machine learning is a very new concept and not many universities offer to teach it. My school and a few others have been utilizing Databricks as one of the tools to teach and learn machine learning. By doing this, my university is creating a strong future workforce for the job market.

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Ann Le

Freelance Translator

ZOO Digital Group plcEntertainment, 501-1000 employees

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