3 repositorios
Techniques and memory management strategies used to improve the performance of complex database queries.
Distinct from Cartesian Product Generation: The candidates focus on mathematical set generation or coordinate conversion, whereas this is about database query engine memory management.
Explore 3 awesome GitHub repositories matching data & databases · Query Execution Optimizations. Refine with filters or upvote what's useful.
Memgraph is an in-memory, distributed graph database designed for high-performance labeled property graph management. It utilizes a Cypher query engine for declarative data retrieval and manipulation, providing a scalable knowledge graph backend that integrates vector search and graph traversals. The system distinguishes itself as a real-time graph analytics platform, employing native C++ and CUDA implementations to execute complex network analysis and dynamic community detection on streaming data. It provides specialized support for AI integration, including GraphRAG capabilities, the constr
The product optimizes caching of record branches to balance query performance against memory.
Rusqlite is an embedded database interface and relational database driver that provides a client library for interacting with SQLite. It functions as an SQL query wrapper, enabling the management of local file-based or in-memory databases through a safe interface. The library allows for the extension of native database capabilities by implementing custom scalar functions, collations, and virtual tables. It also supports the embedding of the database engine directly into the application binary to remove external library dependencies. The project covers a broad range of capabilities including
Implements performance optimizations including prepared statements and lazy row streaming to minimize resource consumption.
This project is a high-performance tabular data processing framework for R, designed to handle massive datasets with memory efficiency and speed. It provides an enhanced data structure that utilizes reference semantics and in-place modification to perform complex transformations without the overhead of unnecessary object copying. The library distinguishes itself through its low-level architectural optimizations, including multi-threaded parallel processing, radix-based sorting, and memory-mapped file parsing. By offloading critical data manipulation and aggregation routines to compiled C code
Applies automatic indexing and internal performance enhancements to accelerate filtering, grouping, and sorting.