Hazelcast Office Hours: Boosting Similarity Search with Real-time Stream Processing

The goal of similarity search and vector databases is to find similar results to the search query for unstructured data, such as text, images, and videos. Here’s an overview:

• Unstructured data is first vectorized and stored in a vector format
• Tools are available to create vectors from unstructured data
• Vector databases store and facilitate similarity searches
• Vector databases enhance high-performance vector search apps
• Combine stream processing with vector search to overcome vector database challenges
  

In our March Office Hours, we discuss how Real-time compute APIs optimize processing capabilities in a distributed cluster to maximize performance gains. The synergy of Real-time storage and computing enables real-time use cases at any scale.

Join us for a 45-minute talk followed by a 15-minute Q&A. Send your questions in advance to [email protected].

Presented By

Fawaz Ghali

Principal Data Science Architect and Head of Developer Relations

Hazelcast

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