Likelihood to Recommend 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 The prerequisite is that you have a supported database/data warehouse and have already found a way to ingest your raw data. Then dbt is very well suited to manage your transformation logic if the people using it are familiar with SQL. If you want to benefit from bringing engineering practices to data, dbt is a great fit. It can bring CI/CD practices, version control, automated testing, documentation generation, etc. It is not so well suited if the people managing the transformation logic do not like to code (in SQL) but prefer graphical user interfaces.
Read full review Pros 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 dbt supports version control through GIT, this allows teams to collaborate and track the data transformation logic. dbt allows us to build data models which helps to break complex transformation logic into simple and smaller logic. dbt is completely based on SQL which allows data analyst and data engineers to build the transformation logic. dbt can be easily integrated with snowflake. Read full review Cons 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 Field-level lineage (currently at table level) Documentation inheritance - if a field is documented the downstream field of the same name could inherit the doc info Adding python model support (in beta now) Read full review Usability 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.
Read full review It requires proficiency with SQL coding and with git practices, but with these prerequisites, it is easy to use. Especially with the dbt cloud, you get a nice interface that makes all the administrative tasks like scheduling jobs quite easy. I also like the built-in SQL editor with syntax highlighting and auto-completion.
Read full review Support Rating 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 Alternatives Considered 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 I actually don't know what the alternative to dbt is. I'm sure one must exist other than more 'roll your own' options like Apache Airflow, say, bu tin terms of super easy managed/cloud data transforms, dbt really does seem to be THE tool to use. It's $50/month per dev, BUT there's a FREE version for 1 dev seat with no read-only access for anyone else, so you can always start with that and then buy yourself a seat later.
Read full review Return on Investment 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 Simplified our BI layer for faster load times Increased the quality of data reaching our end users Makes complex transformations manageable Read full review ScreenShots