DOAG – Databases. Dusseldorf, Germany, May 15-16, 2024

The DOAG 2024 Database with Exaday will once again take place at the Van der Valk Airport Hotel in Düsseldorf from May 15 to 16, 2024 with interesting topics related to databases.

The program is published. Early bird tickets are available until April 17.


Databases: Oracle Database, PostgreSQL, MySQL

With the Oracle 23c database version, we get additional features and special features, which we will take a closer look at together with you: What are the benefits and opportunities? How can performance be optimised and user productivity increased? In addition, hybrid cloud, multicloud, OCI and OSC will be covered, as well as migration, project experiences and lifecyle will be taken into account. What’s new in PostgreSQL and MySQL? You will find the answers at this event.


AI Vector Search is a critical component in the Generative AI Ecosystem. It enables fast and highly accurate similarity search of unstructured content, such as images and documents, by encoding them as high-dimensional vectors created from pre-trained ML embedding models. Each dimension in a vector represents some attribute/characteristic of some content, with the overall vector capturing that content’s semantic meaning. Search by semantics can be significantly faster and more accurate than search by precision, as is typically done in databases today. Oracle is introducing AI Vector Search in the database to enable enterprise companies to combine their business data queries with vector search capabilities to build sophisticated and modern generative-AI applications. For example, it enables applications to combine their business data with large language models (LLMs), like Chat-GPT, in a technique called Retrieval Augmentation Generation (RAG), to deliver highly accurate responses to natural language questions without exposing the data outside of the database.

Shasank Chavan is the Vice President of the Data, In-Memory and AI Technologies group at Oracle. He leads an organization of brilliant engineers working on the nexus between AI systems and modern databases. His team is currently hyper-focused on developing the next-generation, AI-centric data storage engine, designed for in-memory OLTP, Analytics and Vector Search capabilities to power the AI and Generative AI revolution to come. Shasank earned his BS/MS in Computer Science at the University of California, San Diego. He has accumulated more than 40 patents over a span of 25 years working on systems software technology.

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