Elastic, a Search AI company, today announced Search AI Lake, a cloud-native architecture optimized for real-time, low-latency applications including search, retrieval augmented generation (RAG), observability and security. The Search AI Lake also powers the new Elastic Cloud Serverless offering. All operations, from monitoring and backup to configuration and sizing, are managed by Elastic – users just bring their data and choose Elasticsearch, Elastic Observability, or Elastic Security on Serverless. Benefits include:
- Fully decoupling storage and compute enables scalability and reliability using object storage, dynamic caching supports high throughput, frequent updates, and interactive querying of large data volumes.
- Multiple enhancements maintain query performance even when the data is safely persisted on object stores.
- By separating indexing and search at a low level, the platform can automatically scale to meet the needs of a wide range of workloads.
- Users can leverage a native suite of AI relevance, retrieval, and reranking capabilities, including a native vector database integrated into Lucene, open inference APIs, semantic search, and first- and third-party transformer models, which work with the array of search functionalities.
- Elasticsearch’s query language, ES|QL, is built in to transform, enrich, and simplify investigations with fast concurrent processing irrespective of data source and structure.
