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Author: Bob Tabor

articles/azure-cache-for-redis/cache-overview-vector-similarity.md

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+---
+title: What is Vector Similarity in Azure Cache for Redis?
+description: Learn about Azure Cache for Redis to store vector embeddings and provide similarity search.
+author: flang-msft
+ms.author: franlanglois
+ms.service: cache
+ms.topic: overview
+ms.date: 09/18/2023
+---
+
+# What is Vector Similarity in Azure Cache for Redis?
+
+You could rename this "about". Overview documents contain "nice-to-know" information,
+like background information, that is not strictly required to complete a task, but
+builds the readers confidence in the technology, when to use it, etc.
+
+I stole this from your tutorial ... we can break this up and expand on it throughout
+this document:
+
+```markdown
+Azure Cache for Redis can be used to store the embeddings vectors and to perform the vector similarity search. Redis is extremely fast because it runs in-memory. This can be very useful when processing large datasets!
+Because Redis is so popular, it is often already used in applications for caching or session store applications. Redis can often be an economical choice because it can pull double-duty by handling typical caching roles while simultaneously handling vector search applications.
+
+Redis has access to a wide range of search capabilities through the [RediSearch module](cache-redis-modules#redisearch), which is available in the Enterprise tier of Azure Cache for Redis. Vector search capabilities include:
+- Support for `Euclidean`, `Cosine`, and `Internal Product` search distance metrics
+- `FLAT` and `Hierarchical Navigable Small World (HNSW)`  indexing methods
+- Hybrid filtering with [powerful query features](https://redis.io/docs/interact/search-and-query/)
+```
+
+## What is a vector database?
+
+It might be nice to level set here. This would contextualize this article for those
+who may not be familiar with LLMs, embeddings, vectors, nearest neighbor / cosine
+similarity searches, etc. You don't have to go deep.
+
+Alternatively, you could create the section "Who is this for?" but that seems a bit
+more uncouth.
+
+## When should I use it?
+
+You could rename this to "key scenarios". When does it make sense to use Redis
+in this capacity -- as a vector database?
+
+### How does it work?
+
+This is where you could talk about requirements and some light discussion of the
+components in Redis that are employed that provide this functionality. Discuss
+the "under the hood" architecture to help provide insights and understanding, 
+including a discussion of limitations and why a given limitation exists.
+
+
+### Why choose Azure Cashe for Redis for storing and searching for vectors?
+
+What are some of the benefits of using Redis for vectors? You named off a few
+the other day ...
+
+- First to provide this feature
+- Fast / in-memory
+- Inexpensive, esp. if you already have Redis as a component of your application architecture
+- Etc.
+
+
+### What are my other options for storing and searching for vectors?
+
+I personally believe that one of the most difficult things about Azure (and Microsoft
+all up) is the *paradox of choice*. With so many technology options at your disposal
+that can perform a similar role in a system architecture, which stack of technologies 
+should I use? In the previous section, you told the reader why Redis makes the most
+sense. But to be even handed, its not always the right decision. So, if you can
+help the reader find other solutions, you've done them a great service.
+
+### Troubleshooting
+
+You may want to just point out the top one or two scenarios you've come across
+in testing that trip up users. Point them to most extensive documentation on Redis'
+site.