6 Ratings
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Score 8.3 out of 100
24 Ratings
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Score 8.5 out of 100

Likelihood to Recommend

Amazon Tensor Flow

A well-suited scenario for using AWS Tensor Flow is when having a project with a geographically dispersed team, a client overseas and large data to use for training. AWS Tensor Flow is less appropriate when working for clients in regions where it hasn't been allowed yet for use. Since smaller clients are in regions where AWS Tensor Flow hasn't been allowed for use, and those clients traditionally don't have enough hardware, this situation deters a wider use of the tool.
Mauricio Quiroga-Pascal Ortega | TrustRadius Reviewer

Databricks Lakehouse Platform

Databricks has helped my teams write PySpark and Spark SQL jobs and test them out before formally integrating them in Spark jobs. Through Databricks we can create parquet and JSON output files. Datamodelers and scientists who are not very good with coding can get good insight into the data using the notebooks that can be developed by the engineers.
Anonymous | TrustRadius Reviewer

Feature Rating Comparison

Platform Connectivity

Amazon Tensor Flow
Databricks Lakehouse Platform
8.3
Connect to Multiple Data Sources
Amazon Tensor Flow
Databricks Lakehouse Platform
9.0
Extend Existing Data Sources
Amazon Tensor Flow
Databricks Lakehouse Platform
9.0
Automatic Data Format Detection
Amazon Tensor Flow
Databricks Lakehouse Platform
7.0

Data Exploration

Amazon Tensor Flow
Databricks Lakehouse Platform
6.0
Visualization
Amazon Tensor Flow
Databricks Lakehouse Platform
6.0
Interactive Data Analysis
Amazon Tensor Flow
Databricks Lakehouse Platform
6.0

Data Preparation

Amazon Tensor Flow
Databricks Lakehouse Platform
8.0
Interactive Data Cleaning and Enrichment
Amazon Tensor Flow
Databricks Lakehouse Platform
8.0
Data Transformations
Amazon Tensor Flow
Databricks Lakehouse Platform
9.0
Data Encryption
Amazon Tensor Flow
Databricks Lakehouse Platform
7.0
Built-in Processors
Amazon Tensor Flow
Databricks Lakehouse Platform
8.0

Platform Data Modeling

Amazon Tensor Flow
Databricks Lakehouse Platform
8.3
Multiple Model Development Languages and Tools
Amazon Tensor Flow
Databricks Lakehouse Platform
9.0
Automated Machine Learning
Amazon Tensor Flow
Databricks Lakehouse Platform
8.0
Single platform for multiple model development
Amazon Tensor Flow
Databricks Lakehouse Platform
9.0
Self-Service Model Delivery
Amazon Tensor Flow
Databricks Lakehouse Platform
7.0

Model Deployment

Amazon Tensor Flow
Databricks Lakehouse Platform
7.5
Flexible Model Publishing Options
Amazon Tensor Flow
Databricks Lakehouse Platform
7.0
Security, Governance, and Cost Controls
Amazon Tensor Flow
Databricks Lakehouse Platform
8.0

Pros

Amazon Tensor Flow

  • Amazon Elastic Compute Cloud (EC2) allows resizable compute capacity in the cloud, providing the necessary elasticity to provide services for both, small and medium-sized businesses.
  • Tensor Flow allows us to train our models much faster than in our on-premise equipment.
  • Most of the pre-trained models are easy to adapt to our clients' needs.
Mauricio Quiroga-Pascal Ortega | TrustRadius Reviewer

Databricks Lakehouse Platform

  • Extremely Flexible in Data Scenarios
  • Fantastic Performance
  • DB is always updating the system so we can have latest features.
Anonymous | TrustRadius Reviewer

Cons

Amazon Tensor Flow

  • SageMaker isn't available in all regions. This is complicated for some clients overseas.
  • For larger instances, when using a GPU, it takes a while to talk to a customer service representative to ask for a limit increase. Given this, it's recommendable to ask in advance for a limit increase in more expensive and larger cases; otherwise, SageMaker will set the limit to zero by default.
  • Since the data has to be stored in S3 and copied to training, it doesn't allow to test and debug locally. Therefore, we have to wait a lot to check everything after every trail.
Mauricio Quiroga-Pascal Ortega | TrustRadius Reviewer

Databricks Lakehouse Platform

  • The navigation through which one would create a workspace is a bit confusing at first. It takes a couple minutes to figure out how to create a folder and upload files since it is not the same as traditional file systems such as box.com
  • Also, when you create a table, if you forgot to copy the link where the table is stored, it is hard to relocate it. Most of the time I would have to delete the table and re-created.
Ann Le | TrustRadius Reviewer

Usability

Amazon Tensor Flow

No score
No answers yet
No answers on this topic

Databricks Lakehouse Platform

Databricks Lakehouse Platform 9.0
Based on 1 answer
This has been very useful in my organization for shared notebooks, integrated data pipeline automation and data sources integrations. Integration with AWS is seamless. Non tech users can easily learn how to use Databricks. You can have your company LDAP connect to it for login based access controls to some extent
Anonymous | TrustRadius Reviewer

Alternatives Considered

Amazon Tensor Flow

Microsoft Azure is better than Amazon Tensor Flow because it provides easier and pre-built capabilities such as Anomaly Detection, Recommendation, and Ranking.AWS is better than IBM Watson ML Studio because it has direct and prebuilt clustering capabilities AWS, like IBM Watson ML Studio, has powerful built-in algorithms, providing a stronger platform when comparing it with MS Azure ML Services and Google ML Engine.
Mauricio Quiroga-Pascal Ortega | TrustRadius Reviewer

Databricks Lakehouse Platform

Easier to set up and get started. Less of a learning curve.
Anonymous | TrustRadius Reviewer

Return on Investment

Amazon Tensor Flow

  • Positive: It has allowed us to work with our overseas teams without any large hardware investing.
  • Positive: Pre-trained models significantly reduce the time to develop solutions for our clients.
  • Negative: Since it's a relatively new tool, you have to be careful about not paying for large errors while learning to use the tool.
Mauricio Quiroga-Pascal Ortega | TrustRadius Reviewer

Databricks Lakehouse Platform

  • Rapid growth of analytics within our company.
  • Cost model aligns with usage allowing us to make a reasonable initial investment and scale the cost as we realize the value.
  • Platform is easy to learn and Databricks provides excellent support and training.
  • Platform does not require a large DevOPs investment
Anonymous | TrustRadius Reviewer

Pricing Details

Amazon Tensor Flow

General

Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No

Amazon Tensor Flow Editions & Modules

Additional Pricing Details

Databricks Lakehouse Platform

General

Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No

Databricks Lakehouse Platform Editions & Modules

Edition
Standard$0.071
Premium$0.101
Enterprise$0.131
  1. Per DBU
Additional Pricing Details

Rating Summary

Likelihood to Recommend

Amazon Tensor Flow
9.0
Databricks Lakehouse Platform
8.9

Usability

Amazon Tensor Flow
Databricks Lakehouse Platform
9.0

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