Compare the Top Query Engines that integrate with LanceDB as of October 2025

This a list of Query Engines that integrate with LanceDB. Use the filters on the left to add additional filters for products that have integrations with LanceDB. View the products that work with LanceDB in the table below.

What are Query Engines for LanceDB?

Query engines are software tools designed to retrieve and process data from databases or large datasets in response to user queries. They efficiently interpret and execute search requests, optimizing the retrieval process to deliver accurate and relevant results quickly. Query engines can handle structured, semi-structured, and unstructured data, making them versatile for various applications such as data analytics, business intelligence, and search engines. They often support complex query languages like SQL and can integrate with multiple data sources to provide comprehensive insights. By optimizing data retrieval, query engines enhance the performance and usability of data-driven applications and decision-making processes. Compare and read user reviews of the best Query Engines for LanceDB currently available using the table below. This list is updated regularly.

  • 1
    Databricks Data Intelligence Platform
    The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. The winners in every industry will be data and AI companies. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals. Databricks combines generative AI with the unification benefits of a lakehouse to power a Data Intelligence Engine that understands the unique semantics of your data. This allows the Databricks Platform to automatically optimize performance and manage infrastructure in ways unique to your business. The Data Intelligence Engine understands your organization’s language, so search and discovery of new data is as easy as asking a question like you would to a coworker.
  • 2
    DuckDB

    DuckDB

    DuckDB

    Processing and storing tabular datasets, e.g. from CSV or Parquet files. Large result set transfer to client. Large client/server installations for centralized enterprise data warehousing. Writing to a single database from multiple concurrent processes. DuckDB is a relational database management system (RDBMS). That means it is a system for managing data stored in relations. A relation is essentially a mathematical term for a table. Each table is a named collection of rows. Each row of a given table has the same set of named columns, and each column is of a specific data type. Tables themselves are stored inside schemas, and a collection of schemas constitutes the entire database that you can access.
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