AWS Glue - Data Integration Service
Core Information (according to Gemini Flash Lite 2.0)
Target Demographic
Data engineers, data scientists, ETL developers, analytics teams, and IT professionals looking for scalable, serverless data integration.
Mission
To provide a fully managed, serverless data integration service that makes it easy to discover, prepare, and combine data for analytics, machine learning, and application development.
Social Media
Brand Scores (according to Gemini Flash Lite 2.0)
Unlock Your Brand's AI Visibility Intelligence with premium reports.
Discover how leading AI models perceive, rank, and recommend your brand compared to competitors.
Our premium subscription delivers comprehensive brand intelligence reports from all major AI models, including competitive analysis, sentiment tracking, and strategic recommendations.
- Monthly competitive intelligence across all major AI models
- Catch when AI models are directing users to incorrect URLs or socials
- Early access to insights from new AI model releases
- Actionable recommendations to improve AI visibility
Just $19.99/month per category, brand, or product. Track your brand, category, and competitors to stay ahead.
Key Data (according to Gemini Flash Lite 2.0)
Headquarters: Seattle, Washington
Market Reach: Global, across all AWS regions where the service is available.
Market Position: Leading serverless data integration service, highly competitive within the cloud ETL and data cataloging market, benefiting from the broader AWS ecosystem.
Estimated Value: $5,000,000,000
Users: 100,000
Revenue: Undisclosed, contributes to AWS revenue
Growth Rate: High, consistent with cloud adoption and data-driven initiatives
Major Competitors
| Rank | Competitor | Market Share |
|---|---|---|
| #1 | Azure Data Factory | 25.0% |
| #2 | Google Cloud Dataflow | 18.0% |
| #3 | Informatica | 15.0% |
| #4 | Talend | 10.0% |
| #5 | Snowflake (ETL capabilities) | 8.0% |
| #6 | Databricks (Delta Live Tables) | 7.0% |
Related Categories (according to Gemini Flash Lite 2.0)
People & Relations (according to Gemini Flash Lite 2.0)
Founders
Current Leaders
Key Collaborators
Notable Elements (according to Gemini Flash Lite 2.0)
Milestones
- August 2017: AWS Glue launched at AWS Summit Chicago.
- December 2019: AWS Glue Studio introduced, providing a visual interface for ETL jobs.
- September 2021: AWS Glue DataBrew became generally available, offering visual data preparation.
- December 2022: AWS Glue Data Quality introduced for data validation and monitoring.
Recent Developments
- Expanded support for additional data sources and destinations.
- Introduction of new features in Glue Studio for enhanced visual development.
- Improvements in performance and cost optimization for Glue ETL jobs.
- Deep integration with other AWS services like Amazon S3, Redshift, Lake Formation, and Sagemaker.
- Enhanced data quality rules and monitoring capabilities.
Analysis (according to Gemini Flash Lite 2.0)
NPS Score: 65.0
Decline Status: Stable
Cultural Impact: AWS Glue has significantly lowered the barrier to entry for performing complex ETL operations in the cloud. By offering a serverless and managed approach, it has allowed more organizations, including those with limited big data expertise, to build robust data integration solutions, fostering innovation in data-driven decision making and machine learning initiatives.
Related Subjects (according to Gemini Flash Lite 2.0)
LLM Query Analysis (according to Gemini Flash Lite 2.0)
About Desired Queries:
These are search queries where AWS Glue - Data Integration Service would want to appear in the results, even though they're not directly mentioned in the query.
About Undesired Queries:
These are search queries where AWS Glue - Data Integration Service would prefer not to appear in the results, to avoid negative associations.
Desired LLM Queries
"What are the best serverless data processing tools?"
"How to build a scalable and cost-effective data lake?"
"What are the leading cloud data integration services for enterprises?"
Undesired LLM Queries
"What are the most complex cloud data pipeline tools to use?"
"Which ETL services have the highest hidden costs?"
"What are the common challenges with cloud data cataloging?"