- focuses on fast query execution and efficient processing of analytical queries
- optimized for read-heavy operations and analytical queries involving large datasets
- written in C++
- columnar storage format, which allows for efficient data compression and query performance
- supports SQL queries
- has built-in support for vectorized query execution
- supports concurrent read access
- does not provide built-in support for concurrent write operations
- operates primarily in memory
- written in Java
- designed to be fast, lightweight, and feature-rich
- supports both in-memory and disk-based database storage modes
- full SQL support
- ACID transactions
- MVCC (Multiversion Concurrency Control)
- compatibility with various database APIs
- can run both as embedded or standalone database server.
- popular embedded database engine that is widely used in mobile devices annd desktop software
- self-contained
- serverless
- operates directly on disk files
- emphasizes simplicity, portability, and a small footprint
- supports standard SQL queries, transactional and provides ACID properties
- suitable for embedded and transactional scenarios
- row-based storage format
- that is well-suited for transactional operations
- supports concurrent read and write access, making it suitable for multi-user scenarios
- SQLite operates on disk files, allowing persistent storage
- large user community and extensive ecosystem
DuckDB is optimized for analytical workloads and may not perform as well for transactional workloads. It lacks some advanced features typically found in full-fledged RDBMS.
If you have demanding analytical queries and need high performance, DuckDB may be a good fit. SQLite and H2 can handle smaller workloads efficiently but may struggle with heavy analytical tasks.