Azure Data Factory (Microsoft)
Core Information (according to Gemini Flash Lite 2.0)
Category
Cloud Data Integration Service
Founded
January 1, 2015
Location
Redmond, WashingtonWebsite
azure.microsoft.comTarget Demographic
Data engineers, data scientists, and businesses of all sizes that need to integrate data from various sources.
Mission
To provide a fully managed, serverless data integration service that empowers data engineers to easily build and manage data pipelines for all their data integration needs.
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: Redmond, Washington
Market Reach: Global. Azure Data Factory is available in numerous Azure regions worldwide, serving a global customer base.
Market Position: Strong. Azure Data Factory holds a significant position in the cloud data integration market, competing effectively with other major providers.
Estimated Value: $5,000,000,000
Users: 100,000
Revenue: Estimated to be in the hundreds of millions to billions USD annually, based on Azure's overall revenue and market share.
Growth Rate: High. The market for cloud-based data integration is rapidly growing, and Azure Data Factory is experiencing substantial user and revenue growth.
Major Competitors
| Rank | Competitor | Market Share |
|---|---|---|
| #1 | AWS Glue | 40.0% |
| #2 | Informatica Cloud Data Integration | 20.0% |
| #3 | IBM DataStage | 15.0% |
| #4 | Talend Cloud | 10.0% |
| #5 | Google Cloud Dataflow | 8.0% |
| #6 | Apache NiFi | 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
- Public Preview (2015)
- General Availability (2016)
- Continuous updates and feature releases, including data flows and integration with other Azure services
- Introduction of serverless compute options
Recent Developments
- Enhanced support for data flows, allowing for code-free data transformation.
- Integration with Azure Synapse Analytics for seamless data warehousing and analytics.
- New connectors and improved compatibility with various data sources.
- Improvements to pipeline monitoring and management tools.
- Support for Git integration for enhanced collaboration and version control.
Analysis (according to Gemini Flash Lite 2.0)
NPS Score: 35.0
Decline Status: Low. The platform is constantly evolving. The likelihood of decline is low unless there is a significant shift in market preference towards alternative solutions or a major disruption in the cloud data integration landscape.
Cultural Impact: Azure Data Factory's impact is primarily in the realm of data engineering and cloud computing, supporting the shift towards data-driven decision-making across various industries. It has facilitated the adoption of cloud-based data solutions and has become a key component in modern data architectures.
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 Azure Data Factory (Microsoft) 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 Azure Data Factory (Microsoft) would prefer not to appear in the results, to avoid negative associations.
Desired LLM Queries
"How to build an automated data pipeline?"
"What are the best practices for cloud data integration?"
"How do I choose a data integration tool?"
Undesired LLM Queries
"Is Azure Data Factory difficult to learn?"
"What are the common problems with Azure Data Factory?"
"What are the limitations of Azure Data Factory?"