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
ER/Studio
Score 9.9 out of 10
N/A
ER/Studio is a database development and management tool from Embarcadero Technologies (acquired by Idera) in California.
$1,470.40
one-time fee per user
Pricing
AWS Glue
ER/Studio
Editions & Modules
per DPU-Hour
$0.44
billed per second, 1 minute minimum
No answers on this topic
Offerings
Pricing Offerings
AWS Glue
ER/Studio
Free Trial
No
Yes
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
—
Pricing for new customers only, first year maintenance included. Maintenance includes access to technical support and product updates for the defined period of the agreement.
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.
Data Architect is well suited at organizations of all sizes. It is never too early or unnecessary to enforce proper modelling and design standards on data solutions, and this tool will help that greatly by providing an industry leading data modelling tool, ability to import ETL mappings for data lineage, enforcing and managing naming conventions through the naming convention tool, and publishing of data dictionaries through the report publisher. I was successfully able to build models, provide traceability, and document source to target with lineage throughout for both the business (by providing business definitions in the descriptions), and technical teams (by documenting ETL instructions in text fields) along with field level mapping (by creating "Attachments" representing data sources, tables, and fields) providing easy search capabilities using business friendly terms
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.
ER/Studio has the ability to provide consistent field names and data types through domains, which are templates. This provides a way to have consistent naming of common fields, like CreatedBy and the data types for the fields. They also have the ability to change all the fields that use that domain to a different data type.
ER/Studio provides the ability to create custom macros. These macros can be used to apply everything from standard fields based on domains to naming all constraints and indexes. I've also used a macro that comes with ER/Studio to spell check field and table names.
My favorite feature is the ability to compare your data model to databases for deployments of changes, and to other data models.
ER\Studio licensing can be cumbersome and upgrading from one version to another usually takes several phone calls and emails to the licensing group to get the update installed and running.
The repository can be slow when the model count gets larger. By large I mean 20 to 30 models.
A nice feature that I would like to see is table comments be displayed on the model along with the attributes. Currently you have to choose between the two.
While easy to set up and manage monitoring for large datasets, its complexity can be a barrier for new users. Integration with AWS Ecosystem, Managed Monitoring, Dashboards and monitoring tools for AWS Glue are generally easy to set up and maintain, Automated Data Pipelines. Automates data pipeline creation, making it efficient for certain data integration
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.
I can call or email support and both get quick turn around. The only issue is they are on the west coast (US) and have a west coast work schedule and I'm on the East coast.
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.
We are using GLUE for our ETL purpose. it’s ease with other our AWS services makes our ROI, 100% ROI.
One missing piece was compatibility with other data source for which we found a work around and made our data source as S3 only, so our dependencies on other data source is also reducing
ER/Studio has had a positive impact on my project as we can develop the data model and have a clear understanding of business needs before we continue with the development phase.
