AWS Glue vs s3-lambda: What are the differences?

AWS Glue is Amazon's managed ETL service, while s3-lambda is a framework for deploying serverless AWS Lambda functions to process data stored in Amazon S3. Let's explore the key differences between them.

1. Data Transformation Capabilities: AWS Glue is a fully managed extract, transform, and load (ETL) service that allows easy data transformation and integration. It provides a graphical interface to create ETL jobs and supports various data formats, field mapping, and complex transformations. On the other hand, S3-Lambda is a serverless compute service that automatically triggers code when objects are added or modified in Amazon S3. While it supports data processing workflows using Lambda functions, it does not offer the comprehensive data transformation capabilities of Glue.

2. Data Catalog and Schema Discovery: AWS Glue includes a centralized metadata repository, known as the Data Catalog, which automatically discovers, catalogs, and tracks metadata changes in data sources. It enables schema discovery and automatically generates ETL scripts for data transformation. In contrast, S3-Lambda does not provide a built-in data catalog or schema discovery features. Developers would need to implement their own mechanisms for schema management and tracking metadata changes.

3. Job Orchestration and Scheduling: AWS Glue offers built-in job orchestration and scheduling features, allowing users to schedule, monitor, and manage dependencies between ETL jobs. Users can define triggers and workflows to control the execution of ETL tasks. In contrast, S3-Lambda is primarily a serverless compute service for processing individual S3 events. While it can be used to trigger code based on S3 events, it lacks the sophisticated job orchestration and scheduling capabilities provided by Glue.

4. Data Source Connectivity: AWS Glue provides native connectivity to a wide range of data sources, including relational databases, Amazon S3, DynamoDB, and more. It supports connecting to external data sources via JDBC and ODBC connectors. S3-Lambda, on the other hand, primarily focuses on processing data stored in Amazon S3 buckets. While it can interact with other AWS services like AWS Lambda, it does not have native support for various data sources like Glue.

5. Data Lineage and Impact Analysis: AWS Glue captures and records data lineage information, allowing users to track the flow of data across ETL jobs, transformations, and data sources. It provides visibility into the impact analysis of changes to data sources and helps ensure data accuracy and compliance. Conversely, S3-Lambda does not offer built-in capabilities for data lineage and impact analysis. It primarily focuses on serverless compute for processing S3 events rather than providing comprehensive data governance features.

6. Advanced Data Transformation Features: AWS Glue includes advanced data transformation features like automatic schema evolution, type inference, and inferred partitioning capabilities. These features simplify the process of schema evolution in data lakes and provide powerful options for optimizing data queries and performance. While S3-Lambda allows custom code execution on S3 events, it does not offer the same level of built-in advanced data transformation capabilities as Glue.

In summary, AWS Glue is a full-fledged ETL service with comprehensive features for data integration and transformation. S3-Lambda primarily serves as a serverless computing service for processing S3 events with limited data governance capabilities.