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
Toad Data Point
Score 7.8 out of 10
N/A
Toad Data Point is a cross-platform, self-service, data-integration tool that simplifies data access, preparation and provisioning. It provides data connectivity and desktop data integration, and with the Workbook interface for business users, it provides simple-to-use visual query building and workflow automation.
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.
Appropriate for general querying and some DBA work. It's the universal least-offensive solution for most environments - not best of breed, but not subject to unusual/extensive requirements. It just works. On the other hand, some functionality (e.g. data import/export, snippets) are perfunctory and minimal and seem to be either difficult or impossible to automate. If you need to streamline those operations, you'll be forced to rely on third-party solutions that mostly work on top of (instead of with) TOAD.
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.
The workflow is a relatively new feature. Quest is adding additional functionality and the workflows are useful now.
Would be nice if the 'Automate' feature was a bit easier to use.
Would be nice if some of the SQL Editor features in the traditional interface worked better in the new workflow interface (although, these are being fixed with each release).
We give 7 rating because of usefulness in AWS world without worrying about infrastructure and services interaction, it’s pretty out of the box gives us the flexibility to interact with them and use them. we take the data source in s3 from external system and then transform it using other AWS services and putting it back for other external services to consume in S3 form.
I find Toad Data Point easy to use for both the novice and the experienced business analyst. If all you desire is to access data and create spreadsheets...this is a snap. Toad Data Point actually has cool data analysis features built into it. The newer workflow interface makes automating steps a snap
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.
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.
It is the least common denominator - not particularly optimized for our environment or workflows.
Hangs or slowdowns add anywhere from 5% - 7% for projects utilizing large/complicated data setts. (This could be due to other IT-imposed constraints and not entirely due to TOAD.)
Trying to perform some operations requires reading documentation and experimenting in order to figure out the TOAD-specific approaches and commands.
It just works (when we understand it). Updates don't break things and things don't suddenly start behaving differently. Best of all, we don't mysteriously lose functionality.
