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Product > Data models

Full-text Data

CrateDB efficiently indexes, stores, and retrieves high volumes of unstructured, semi-structured, and structured data, enabling advanced and fast searches across diverse data types, including full-text data.

Full-text search with SQL

Hyper-fast. Queries in milliseconds.

        
/* The table stores data about netflix movies and series. The composite fulltext 
 * index is defined on two columns with the analyzer based on English language. */
CREATE TABLE "netflix_catalog" (
    "show_id" TEXT PRIMARY KEY,
    "type" TEXT,
    "title" TEXT,
    "director" TEXT,
    "cast" ARRAY(TEXT),
    "country" TEXT,
    "date_added" TIMESTAMP,
    "release_year" TEXT,
    "rating" TEXT,
    "duration" TEXT,
    "listed_in" ARRAY(TEXT),
    "description" TEXT,
    INDEX title_director_description_ft using FULLTEXT (title, director, description) 
    WITH (analyzer = 'english')
);

Full-text search and real-time indexing

Perform quick and accurate searches across various data types, including text, documents, and other unstructured data with robust full-text search capabilities and real-time indexing. CrateDB's fully distributed query engine is built on top of Apache Lucene®. To use full-text search, a full-text index with an analyzer must be created when setting up the column, allowing the text to be broken down into searchable tokens. Once this is done, full-text search queries can be run based on the index.

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Support for complex querying

Perform complex search queries effortlessly using CrateDB's support for advanced techniques, including Boolean logic, wildcard searches, phrase searches, proximity searches, and fuzzy search capabilities. Experience precise and versatile querying options that accommodate variations, ensuring accurate results across diverse search requirements.

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Scalable, high-performance, and distributed search engine

Scale your search operations effortlessly with CrateDB's high-performance and scalable architecture, ensuring rapid indexing and retrieval of search results even when dealing with high volumes of data. Its distributed shared-nothing architecture enables executing distributed full-text searches efficiently across diverse datasets and horizontal scaling to accommodate growing search requirements. 

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Real-time analytics and data ingestion

Utilize real-time data ingestion and analysis, enabling continuous updates and immediate availability of new data in search results.

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High availability and fault tolerance

Ensure high availability of search functionalities with a fault-tolerant design. CrateDB’s built-in mechanisms for automatic failover and replication prevent downtime and ensure uninterrupted search operations.

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Easy and seamless integration

Integrate with various programming languages, frameworks, and tools with native SQL and the PostgreSQL Wire Protocol. Seamlessly integrate CrateDB with various analytical tools, merging search capabilities with analytical processing for comprehensive insights into search results and data patterns. Customize and expand search functionalities using CrateDB's extensible plugin ecosystem, integrating additional modules or third-party plugins as per specific search requirements.

View a sample list of integrations >

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Learn more about the database

Unlocking the Power of Semantic Search

Unlocking the power of semantic search

Unlocking the Power of Semantic Search

Unlock the power of semantic search by watching this insightful webinar where Simon Prickett, Senior Product Evangelist CrateDB, highlights CrateDB's ability to integrate various data types (text, geospatial, vectors) for hybrid search using SQL, enabling faster, more contextually relevant results.

Watch now

CrateDB workshop

CrateDB workshop

Learn how from Karyn Azevedo, Solution Engineer at CrateDB, how to modeling you data in CrateDB.

Timestamp:  25:43–39:27

CrateDB: A database or a search engine? Both!

CrateDB: A database or a search engine? Both!

Learn from Marija Selaković, Developer Advocate at CrateDB, how to get all the benefits of traditional databases while utilizing the scalability and efficiency of a distributed search engine.

Curious to learn more?

Other resources on full-text search

FAQ

Full-text search indexes the entire textual content of documents, articles, or records, making all text fields searchable. This allows users to perform comprehensive searches across large volumes of unstructured or semi-structured text. CrateDB enhances this functionality with its high-performance, scalable architecture, ensuring rapid indexing and efficient retrieval even with substantial data volumes. 

Full-text search techniques include boolean logic, wildcard searches, phrase searches, proximity searches, and fuzzy searches, which enhance the depth and accuracy of search results. CrateDB leverages these capabilities to provide robust full-text search functionality with real-time indexing and efficient query performance.

Full-text search databases allow users to search for words throughout the entire text body of documents, enhancing research depth and precision. Examples of databases optimized for full-text search include CrateDB, MongoDB, Elasticsearch, and PostgreSQL. CrateDB's distributed shared-nothing architecture is built on top of Apache Lucene and excels in performing efficient distributed full-text searches across diverse datasets, ensuring scalability to meet growing search demands.