aid: amazon-glue
name: Amazon Glue
description: Amazon Glue is a serverless data integration service that makes it simple to discover, prepare, move, and integrate
  data from multiple sources for analytics, machine learning, and application development. It provides both visual and code-based
  interfaces for ETL operations and includes a Data Catalog for unified metadata management.
type: Index
image: https://a0.awsstatic.com/libra-css/images/logos/aws_logo_smile_1200x630.png
url: https://raw.githubusercontent.com/api-evangelist/amazon-glue/refs/heads/main/apis.yml
created: '2024-01-15'
modified: '2026-05-19'
specificationVersion: '0.19'
tags:
- Analytics
- AWS
- Data Catalog
- Data Integration
- Data Pipeline
- ETL
- Serverless
apis:
- aid: amazon-glue:amazon-glue-api
  name: Amazon Glue API
  description: The Amazon Glue API enables programmatic access to create and manage ETL jobs, crawlers, data catalogs, connections,
    and development endpoints. You can discover data sources, transform data, and orchestrate data integration workflows across
    multiple data stores.
  humanURL: https://aws.amazon.com/glue/
  baseURL: https://glue.amazonaws.com
  tags:
  - Analytics
  - Data Catalog
  - Data Integration
  - ETL
  properties:
  - type: Documentation
    url: https://docs.aws.amazon.com/glue/latest/dg/aws-glue-api.html
  - type: OpenAPI
    url: openapi/amazon-glue-openapi.yml
  - type: GettingStarted
    url: https://aws.amazon.com/glue/getting-started/
  - type: Pricing
    url: https://aws.amazon.com/glue/pricing/
  - type: FAQ
    url: https://aws.amazon.com/glue/faqs/
  - type: APIReference
    url: https://docs.aws.amazon.com/glue/latest/dg/aws-glue-api.html
  - type: Authentication
    url: https://docs.aws.amazon.com/general/latest/gr/signature-version-4.html
  - type: JSONSchema
    url: json-schema/glue-job-schema.json
  - type: JSONLD
    url: json-ld/amazon-glue-context.jsonld
  - type: NaftikoCapability
    url: capabilities/amazon-glue.yaml
common:
- type: Portal
  url: https://aws.amazon.com/glue/
- type: Documentation
  url: https://docs.aws.amazon.com/glue/
- type: TermsOfService
  url: https://aws.amazon.com/service-terms/
- type: PrivacyPolicy
  url: https://aws.amazon.com/privacy/
- type: Support
  url: https://aws.amazon.com/premiumsupport/
- type: Blog
  url: https://aws.amazon.com/blogs/big-data/tag/aws-glue/
- type: GitHubOrganization
  url: https://github.com/aws
- type: Console
  url: https://console.aws.amazon.com/glue/
- type: SignUp
  url: https://portal.aws.amazon.com/billing/signup
- type: StatusPage
  url: https://health.aws.amazon.com/health/status
- type: Contact
  url: https://aws.amazon.com/contact-us/
- type: SpectralRules
  url: rules/amazon-glue-spectral-rules.yml
- type: Vocabulary
  url: vocabulary/amazon-glue-vocabulary.yaml
- type: Features
  data:
  - name: Serverless ETL
    description: Run ETL jobs without managing infrastructure with automatic scaling and pay-per-use pricing.
  - name: Visual ETL Editor
    description: Build ETL pipelines visually using a drag-and-drop interface without writing code.
  - name: Data Catalog
    description: Unified metadata repository for all data assets across S3, databases, and data warehouses.
  - name: Automated Schema Discovery
    description: Crawlers automatically discover data schemas and populate the Data Catalog.
  - name: Workflow Orchestration
    description: Orchestrate multi-job ETL pipelines with triggers, conditional flows, and scheduling.
  - name: ML Transforms
    description: Use machine learning to automate complex data transformation tasks like entity deduplication.
  - name: Schema Registry
    description: Centrally manage and enforce data schema evolution with versioning and compatibility checks.
  - name: Data Quality
    description: Define and evaluate data quality rules to validate data during ETL processing.
- type: UseCases
  data:
  - name: Data Lake ETL
    description: Build ETL pipelines to ingest, transform, and load data into Amazon S3 data lakes.
  - name: Data Warehouse Loading
    description: Extract and transform data from multiple sources and load into Amazon Redshift.
  - name: Data Catalog Management
    description: Maintain a unified data catalog for data discovery across all data assets.
  - name: Real-Time Streaming ETL
    description: Process streaming data from Kinesis and Kafka with Glue Streaming jobs.
  - name: Machine Learning Data Prep
    description: Prepare and transform training datasets for machine learning using Glue Studio.
- type: Integrations
  data:
  - name: Amazon S3
    description: Primary data lake storage for Glue ETL input and output.
  - name: Amazon Redshift
    description: Load transformed data into Redshift data warehouse.
  - name: Amazon Athena
    description: Query Data Catalog tables directly with Athena serverless SQL.
  - name: Amazon Kinesis
    description: Process streaming data from Kinesis Data Streams with Glue streaming.
  - name: Apache Kafka
    description: Ingest and process Kafka streaming data in Glue jobs.
  - name: AWS Lake Formation
    description: Fine-grained access control to Glue Data Catalog resources.
  - name: Amazon RDS
    description: Connect to relational databases as ETL data sources.
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
  url: https://apievangelist.com