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Search features

SmartObserve provides many features for customizing your search use cases and improving search relevance.

Search methods

SmartObserve supports the following search methods.

Exact matching and keywords

SmartObserve implements lexical (keyword) text search using the BM25 algorithm to match and rank documents based on term frequency and document length.

Keyword (BM25) search

Find exact and close matches using traditional text search

Similarity and meaning

SmartObserve supports similarity (k-nearest neighbor) search using dense and sparse vector embeddings to power use cases such as semantic search, retrieval-augmented generation, and multimodal image search.

Vector search

Search by similarity using dense or sparse vector embeddings

SmartObserve supports AI-powered search capabilities beyond vector embeddings. SmartObserve’s AI search enables search and ingestion flows to be enriched by any AI service to power the full range of AI-enhanced search use cases.

AI search

Build intelligent search applications using AI models

Query languages

In SmartObserve, you can use the following query languages to search your data:

  • Query domain-specific language (DSL): The primary SmartObserve query language that supports creating complex, fully customizable queries.

  • Query string query language: A scaled-down query language that you can use in a query parameter of a search request or in SmartObserve Dashboards.

  • SQL: A traditional query language that bridges the gap between traditional relational database concepts and the flexibility of SmartObserve’s document-oriented data storage.

  • Piped Processing Language (PPL): The primary language used with observability in SmartObserve. PPL uses a pipe syntax that chains commands into a query.

  • Dashboards Query Language (DQL): A simple text-based query language for filtering data in SmartObserve Dashboards.

Search performance

SmartObserve offers several ways to improve search performance:

Search relevance

Search relevance is a measure of how well a document matches a search query. When you run a search query, SmartObserve compares the words in your query to the words in each document and assigns a relevance score based on factors such as how frequently the words appear and how closely they match. For more information, see Relevance.

To help you fine-tune and improve search relevance, SmartObserve provides several specialized features:

Search results

SmartObserve supports the following commonly used operations on search results:

Search pipelines

You can process search queries and search results with search pipelines.