It's Your Data, Master It.
Age
A distributed analytics platform for big data processing.
Apache Age Basics
This course covers the fundamentals of Apache Age, including installation, data modeling, querying, indexing, optimization, and integration with Apache Spark. Participants will gain practical knowledge on how to leverage Apache Age for managing and querying large-scale graph data efficiently.
Advanced Apache Age Techniques
This course delves deeper into Apache Age's advanced features, including advanced querying techniques, graph algorithms, performance tuning, real-world use cases, and integrating with other data stores. Participants will learn how to optimize Apache Age for specific tasks and scenarios.
Apache Age Administration and Management
This course focuses on the administration and management aspects of Apache Age, covering cluster deployment, data backup, security, monitoring, troubleshooting, and scaling deployments. Participants will learn how to effectively manage and maintain Apache Age clusters in production environments.
Apache Age Fundamentals
1. Introduction to Apache Age
2. Understanding Graph Databases
3. Apache Age Architecture
4. Installation and Setup
5. Basic CRUD Operations
6. Querying Graph Data
7. Data Modeling in Apache Age
8. Performance Tuning and Optimization
9. Real-world Applications
10. Conclusion and Next Steps
Apache Age Intermediate
1. Review of Apache Age Fundamentals
2. Advanced Querying Techniques
3. Indexing and Query Optimization
4. Advanced Data Modeling
5. Data Partitioning Strategies
6. Integration with Apache Spark
7. Integration with Apache HBase
8. Security and Authentication
9. Monitoring and Troubleshooting
10. Case Studies and Best Practices
Apache Age Advanced
1. Scaling Apache Age for Large Datasets
2. Distributed Transactions and Consistency
3. Advanced Graph Algorithms
4. Custom Analytics with Apache Age
5. High Availability and Disaster Recovery
6. Advanced Performance Tuning
7. Building Custom Applications
8. Real-time Data Processing with Apache Kafka
9. Machine Learning Integration
10. Future Trends in Graph Databases