Add Elasticsearch to the README (#3688)

Elasticsearch is by far the most widely deployed vector database (https://db-engines.com/en/ranking/vector+dbms) and we were also part of the 1.0 launch.

Signed-off-by: Philipp Krenn <[email protected]>

Author: xeraa

README.md

@@ -25,7 +25,7 @@ You can find more details in the [Reference Documentation](https://docs.spring.i
   - [Moderation](https://docs.spring.io/spring-ai/reference/api/index.html#api/moderation)
 * Portable API support across AI providers for both synchronous and streaming options. Access to [model-specific features](https://docs.spring.io/spring-ai/reference/api/chatmodel.html#_chat_options) is also available.
 * [Structured Outputs](https://docs.spring.io/spring-ai/reference/api/structured-output-converter.html) - Mapping of AI Model output to POJOs.
-* Support for all major [Vector Database providers](https://docs.spring.io/spring-ai/reference/api/vectordbs.html) such as *Apache Cassandra, Azure Vector Search, Chroma, Milvus, MongoDB Atlas, MariaDB, Neo4j, Oracle, PostgreSQL/PGVector, PineCone, Qdrant, Redis, and Weaviate*.
+* Support for all major [Vector Database providers](https://docs.spring.io/spring-ai/reference/api/vectordbs.html) such as *Apache Cassandra, Azure Vector Search, Chroma, Elasticsearch, Milvus, MongoDB Atlas, MariaDB, Neo4j, Oracle, PostgreSQL/PGVector, PineCone, Qdrant, Redis, and Weaviate*.
 * Portable API across Vector Store providers, including a novel SQL-like [metadata filter API](https://docs.spring.io/spring-ai/reference/api/vectordbs.html#metadata-filters).
 * [Tools/Function Calling](https://docs.spring.io/spring-ai/reference/api/tools.html) - permits the model to request the execution of client-side tools and functions, thereby accessing necessary real-time information as required.
 * [Observability](https://docs.spring.io/spring-ai/reference/observability/index.html) - Provides insights into AI-related operations.