PostgreSQL Advanced: Scalability and Sharding (Citus) Training Course

Achieve proficiency in AI integration with Postgres through this instructor-led live training in India. Gain skills in configuring extensions, implementing pgvector embeddings, and connecting LLMs for immediate insights. Enhance query performance and construct intelligent systems within a hands-on live-lab environment.

This 21-hour instructor-led training in India enables data engineers and DBAs to integrate AI models into PostgreSQL. Participants will master the deployment of optimized architectures, the implementation of vector search, and the enforcement of strict governance, ensuring the delivery of secure and high-performance enterprise-grade AI solutions.

This course delves into the foundational aspects of PostgreSQL server extensions and libraries designed to incorporate AI methodologies into database architectures. Key topics include similarity and semantic search leveraging embedding vectors, Text-to-SQL query execution, and Retrieval-Augmented Generation (RAG). Participants will acquire hands-on skills in installing PgVector and PgAI, generating and ingesting vector embeddings, constructing vector indexes, and implementing semantic search alongside RAG workflows. Furthermore, the curriculum guides learners through building Text-to-SQL applications utilizing LangChain with Python or JavaScript. Through demonstrations and practical exercises, the course solidifies these core concepts and technical competencies.

This program explores the essentials of PostgreSQL server extensions that facilitate the integration of AI methodologies into database environments. Special attention is given to similarity and semantic search utilizing embedding vectors. Learners will acquire the skills to install PgVector, handle vector embedding generation and loading, build vector indexes, and apply semantic search strategies. The curriculum reinforces core theoretical knowledge and practical proficiency through interactive demonstrations and hands-on training.

This hands-on course concentrates on the real-world implementation of performance tuning within PostgreSQL. Learners will develop the skills to dissect query execution, refine indexing strategies, fine-tune memory and system parameters, and effectively oversee workload monitoring. Through practical case studies and live practical sessions, the course illustrates techniques for pinpointing and eliminating performance bottlenecks across both database and system layers.

This training offers the core insights necessary to install, set up, and operate PostgreSQL databases proficiently. Learners will grasp the management of user security, execution of backups and restores, log management, and adjustment of fundamental parameters. Through practical assignments, students will apply real-world administrative tasks and get ready for complex areas like performance optimisation and replication.

In this instructor-led live training (onsite or remote), participants will explore both fundamental and advanced PostgreSQL topics, including administration, performance tuning, advanced development, and replication. Through a series of hands-on live lab exercises, participants will gain practical experience in setup, configuration, testing, deployment, and troubleshooting.

Upon completion of this training, participants will be able to:

• Utilize advanced administration techniques to configure and manage a PostgreSQL server.
• Optimize database structures and queries to achieve maximum performance.
• Implement replication and scaling strategies for a PostgreSQL server.

This instructor-led, live training in India is tailored to help advanced DevOps professionals and database engineers implement PostgresAI at scale. Participants will gain proficiency in database cloning, AI-driven query optimization, and monitoring through hands-on exercises in a live-lab setting.

This course offers deep insights into PostgreSQL replication, high availability, and cluster management. Learners will build and manage multi-node environments, set up failover automation, and investigate load balancing and connection pooling solutions. It includes live replication labs and recovery simulations to reinforce learning.