Best Embedded Database Systems for Databricks Data Intelligence Platform
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Compare the Top Embedded Database Systems that integrate with Databricks Data Intelligence Platform as of July 2025
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This a list of Embedded Database systems that integrate with Databricks Data Intelligence Platform. Use the filters on the left to add additional filters for products that have integrations with Databricks Data Intelligence Platform. View the products that work with Databricks Data Intelligence Platform in the table below.
What are Embedded Database Systems for Databricks Data Intelligence Platform?
Embedded database systems are lightweight, self-contained databases that are integrated directly into applications, allowing data management without requiring a separate database server. They are optimized for performance and simplicity, often running within the same process as the host application, making them ideal for use in mobile apps, IoT devices, and small-scale applications. These databases support SQL or other query languages and offer full database functionality, including transaction management and data integrity. Embedded database systems are designed to operate with minimal configuration, providing fast, reliable data storage and retrieval within constrained environments. Their ease of integration and low resource usage make them essential for applications that need efficient local data management without the overhead of external databases. Compare and read user reviews of the best Embedded Database systems for Databricks Data Intelligence Platform currently available using the table below. This list is updated regularly.
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LanceDB
LanceDB
LanceDB is a developer-friendly, open source database for AI. From hyperscalable vector search and advanced retrieval for RAG to streaming training data and interactive exploration of large-scale AI datasets, LanceDB is the best foundation for your AI application. Installs in seconds and fits seamlessly into your existing data and AI toolchain. An embedded database (think SQLite or DuckDB) with native object storage integration, LanceDB can be deployed anywhere and easily scales to zero when not in use. From rapid prototyping to hyper-scale production, LanceDB delivers blazing-fast performance for search, analytics, and training for multimodal AI data. Leading AI companies have indexed billions of vectors and petabytes of text, images, and videos, at a fraction of the cost of other vector databases. More than just embedding. Filter, select, and stream training data directly from object storage to keep GPU utilization high.Starting Price: $16.03 per month -
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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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