nutsdb/nutsdb

Features

• Embedded Key-Value Stores - Provides an embedded key-value store for persisting byte slices within isolated, named buckets.
• Manual Transaction Controls - Provides explicit begin, commit, and rollback methods for direct transaction lifecycle management.
• Complex Data Structure Stores - Organizes data using lists, sets, and sorted sets to handle diverse storage and retrieval requirements.
• Complex Data Structure Stores - Supports high-performance data manipulation of complex types including lists, sets, and sorted sets.
• Disk-Backed Stores - Utilizes memory-mapped files and standard file I/O to persist large datasets on physical disks.
• Append-Only Log Stores - Implements a persistence layer that writes data to an append-only file with an in-memory index for high write throughput.
• Complex Data Type Indexing - Organizes diverse datasets using lists, sets, and sorted sets to enable efficient range scans and membership checks.
• Atomic State Updates - Ensures data consistency and isolation during complex write cycles using serializable transactions and atomic operations.
• ACID-Compliant - Provides a storage engine that ensures atomic, consistent, isolated, and durable operations with crash safety and rollback support.
• Key-Value - Persists data as simple key-value pairs for high-performance access within a transactional context.
• Strict Serializability - Ensures strict data consistency through sequential transaction processing and absolute serializability.
• Transactional Storage Engines - Provides a transactional storage model featuring hot backups and a compaction algorithm to maintain write performance.
• Memory-Mapped I/O - Maps files directly into virtual memory to allow the operating system to handle page caching and disk I/O.
• Byte Sequence Storage - Stores and manages raw binary data sequences as the fundamental unit for key-value storage.
• Cursor-Based Iteration - Traverses entries in forward or reverse order using a cursor to process large datasets efficiently.
• Storage Compaction Utilities - Reclaims storage space and maintains write performance by merging multiple versions of the same key.
• In-Memory Caches - Implements high-speed memory mapped files and time-to-live settings to manage temporary data and reduce latency.
• Key Change Notifications - Provides a watch system to track changes to specific keys and trigger immediate notifications upon updates.
• Prefix-Based Scanning - Retrieves entries using prefix matching, regular expressions, or range-based scans to find specific keys.
• Change Notifications - Monitors specific keys for modifications and triggers notifications when data updates occur.
• List Data Structures - Implements ordered sequence collections supporting efficient push, pop, and range-based operations.
• Log Compaction - Implements log compaction to retain only the latest value for each key, reclaiming space and optimizing reads.
• Memory-Mapped Storage - Provides configurable storage options including memory-mapped files and standard file I/O.
• Set Data Structures - Provides collections of unique elements optimized for membership testing and set-theoretic operations like unions and differences.
• Sorted Sets - Stores unique elements associated with numerical scores to enable efficient range queries and ranking operations.
• Bucket-Based Namespaces - Organizes key-value pairs into named logical containers to separate data domains within a single store.
• Large Dataset Optimizations - Optimizes memory usage and consistency through high-performance compaction algorithms on large-scale data.
• Database Systems - Listed in the “Database Systems” section of the Awesome Go awesome list.

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