AWS Glue vs. Databricks Data Intelligence Platform

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
AWS Glue
Score 7.9 out of 10
N/A
AWS Glue is a managed extract, transform, and load (ETL) service designed to make it easy for customers to prepare and load data for analytics. With it, users can create and run an ETL job in the AWS Management Console. Users point AWS Glue to data stored on AWS, and AWS Glue discovers data and stores the associated metadata (e.g. table definition and schema) in the AWS Glue Data Catalog. Once cataloged, data is immediately searchable, queryable, and available for ETL.
$0.44
billed per second, 1 minute minimum
Databricks Data Intelligence Platform
Score 8.5 out of 10
N/A
Databricks in San Francisco offers the Databricks Lakehouse Platform (formerly the Unified Analytics Platform), a data science platform and Apache Spark cluster manager. The Databricks Unified Data Service aims to provide a reliable and scalable platform for data pipelines, data lakes, and data platforms. Users can manage full data journey, to ingest, process, store, and expose data throughout an organization. Its Data Science Workspace is a collaborative environment for practitioners to run…
$0.07
Per DBU
Pricing
AWS GlueDatabricks Data Intelligence Platform
Editions & Modules
per DPU-Hour
$0.44
billed per second, 1 minute minimum
Standard
$0.07
Per DBU
Premium
$0.10
Per DBU
Enterprise
$0.13
Per DBU
Offerings
Pricing Offerings
AWS GlueDatabricks Data Intelligence Platform
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
AWS GlueDatabricks Data Intelligence Platform
Top Pros
Top Cons
Best Alternatives
AWS GlueDatabricks Data Intelligence Platform
Small Businesses
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10

No answers on this topic

Medium-sized Companies
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.1 out of 10
Snowflake
Snowflake
Score 9.0 out of 10
Enterprises
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.1 out of 10
Snowflake
Snowflake
Score 9.0 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
AWS GlueDatabricks Data Intelligence Platform
Likelihood to Recommend
7.7
(7 ratings)
8.4
(17 ratings)
Usability
-
(0 ratings)
9.5
(3 ratings)
Support Rating
7.0
(1 ratings)
8.6
(2 ratings)
Contract Terms and Pricing Model
-
(0 ratings)
8.0
(1 ratings)
Professional Services
-
(0 ratings)
10.0
(1 ratings)
User Testimonials
AWS GlueDatabricks Data Intelligence Platform
Likelihood to Recommend
Amazon AWS
One of AWS Glue's most notable features that aid in the creation and transformation of data is its data catalog. Support, scheduling, and the automation of the data schema recognition make it superior to its competitors aside from that. It also integrates perfectly with other AWS tools. The main restriction may be integrated with systems outside of the AWS environment. It functions flawlessly with the current AWS services but not with other goods. Another potential restriction that comes to mind is that glue operates on a spark, which means the engineer needs to be conversant in the language.
Read full review
Databricks
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.
Read full review
Pros
Amazon AWS
  • It is extremely fast, easy, and self-intuitive. Though it is a suite of services, it requires pretty less time to get control over it.
  • As it is a managed service, one need not take care of a lot of underlying details. The identification of data schema, code generation, customization, and orchestration of the different job components allows the developers to focus on the core business problem without worrying about infrastructure issues.
  • It is a pay-as-you-go service. So, there is no need to provide any capacity in advance. So, it makes scheduling much easier.
Read full review
Databricks
  • 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
Read full review
Cons
Amazon AWS
  • In-Stream schema registries feature people can not use this more efficiently
  • in Connections feature they can add more connectors as well
  • The crucial problem with AWS Glue is that it only works with AWS.
Read full review
Databricks
  • Connect my local code in Visual code to my Databricks Lakehouse Platform cluster so I can run the code on the cluster. The old databricks-connect approach has many bugs and is hard to set up. The new Databricks Lakehouse Platform extension on Visual Code, doesn't allow the developers to debug their code line by line (only we can run the code).
  • Maybe have a specific Databricks Lakehouse Platform IDE that can be used by Databricks Lakehouse Platform users to develop locally.
  • Visualization in MLFLOW experiment can be enhanced
Read full review
Usability
Amazon AWS
No answers on this topic
Databricks
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
Read full review
Support Rating
Amazon AWS
Amazon responds in good time once the ticket has been generated but needs to generate tickets frequent because very few sample codes are available, and it's not cover all the scenarios.
Read full review
Databricks
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.
Read full review
Alternatives Considered
Amazon AWS
AWS Glue is a fully managed ETL service that automates many ETL tasks, making it easier to set AWS Glue simplifies ETL through a visual interface and automated code generation.
Read full review
Databricks
Compared to Synapse & Snowflake, Databricks provides a much better development experience, and deeper configuration capabilities. It works out-of-the-box but still allows you intricate customisation of the environment. I find Databricks very flexible and resilient at the same time while Synapse and Snowflake feel more limited in terms of configuration and connectivity to external tools.
Read full review
Return on Investment
Amazon AWS
  • It had a positive impact on the way we build our data lake.
  • It is the single source of truth for data structure (schemas/tables/views).
Read full review
Databricks
  • The ability to spin up a BIG Data platform with little infrastructure overhead allows us to focus on business value not admin
  • DB has the ability to terminate/time out instances which helps manage cost.
  • The ability to quickly access typical hard to build data scenarios easily is a strength.
Read full review
ScreenShots