What is AWS Glue?
AWS Glue is an ETL (Extract, Transform, and Load) data integration solution that is fully managed.
The process of preparing and merging data for analytics, machine learning, and application
development is known as data integration. It's made to make it simple and inexpensive to not just
categorize your data, but also to clean, enhance, and transfer it.
2. AWS Glue is a serverless data integration service that
makes it easy to discover, prepare, and combine data
for analytics, machine learning, and application
development. AWS Glue provides all the capabilities
needed for data integration so that you can start
analyzing your data and putting it to use in minutes
instead of months.
What is AWS Glue?
3. USE CASES
Glue can integrate with Snowflake data
warehouse to help manage the data
integration process.
AWS data lake can integrate with Glue.
AWS Glue can integrate with Athena to
create schemas.
ETL code can be used for Glue on GitHub
as well.
4. Benefits of using Glue
Fault-tolerance: Failed jobs in Glue are retrievable, and
logs in Glue can be debugged.
Filtering: Filters for bad data.
Support: Supports several non-native Java Database
Connectivity (JDBC) data sources.
Maintenance and deployment: Simple maintenance
and deployment, because the service is completely
managed by AWS.
5. Drawbacks of
Using Glue
Limited compatibility: While AWS Glue does work with
a variety of commonly used data sources, it only works
with services running on AWS. Organizations may need
a third-party ETL service if sources are not AWS-based.
No incremental data sync: All data is staged on S3 first,
so Glue is not the best option for real-time ETL jobs.
Learning curve: Teams using Glue should have a strong
understanding of Apache spark.
Relational database queries: Glue has limited support
for queries of traditional relational databases, only SQL
queries.
