slatedb/slatedb

Features

• Log-Structured Merge-Trees - Utilizes a log-structured merge-tree architecture to organize data for high-throughput writes and efficient range queries.
• LSM-Tree Key-Value Stores - Implements a log-structured merge-tree key-value store designed specifically for high-throughput writes to remote cloud storage.
• Concurrent Read-Write Transactions - Provides snapshot-based concurrency control to isolate read operations from write operations.
• Copy-on-Write Transaction Systems - Provides a copy-on-write transactional system to create instant, zero-copy dataset snapshots.
• Data Lake Transaction Managers - Provides transactional management with snapshot isolation for workloads operating on cloud-native data lakes.
• Distributed Databases - Provides a distributed database engine core with atomic transactions and snapshots for building scalable data applications.
• Atomic Transactions - Ensures data consistency by grouping multiple operations into atomic transactions.
• Single-Writer Multi-Reader Stores - Implements a single-writer multi-reader model to ensure consistency while scaling concurrent read operations.
• Block Caches - Speeds up data retrieval by storing frequently accessed blocks in memory and on local disk.
• Object Storage Database Engines - Serves as a database backend that persists data directly to cloud object storage while optimizing read performance.
• Object-Storage Persistence - Persists database records directly to cloud object storage for durable, cost-effective, and unlimited scaling.
• Key-Value - Provides a cloud-native key-value database that persists data directly to object storage.
• Change Data Capture - Streams a real-time record of database modifications for synchronization and auditing.
• Read Performance Optimizations - Implements multi-level block caching and bloom filters to reduce latency when retrieving data from cloud object storage.
• Caching and Performance - Optimizes read performance by utilizing block caches and bloom filters to reduce cloud storage latency.
• Transactional Storage Layers - Provides a transactional persistence layer featuring single-writer concurrency control and zero-copy cloning via checkpoints.
• Automatic Background Compactions - Performs automatic background compactions to merge sorted runs and reclaim disk space.
• Data Lakes - Serves as a high-performance indexing layer for large-scale analytical datasets stored in cloud data lakes.
• Bloom Filters - Implements Bloom filters to optimize data retrieval by skipping unnecessary cloud object storage lookups.
• Zero-Copy Cloning - Creates checkpoints to fork or split data sets without duplicating the physical storage on disk.
• Range Query Structures - Supports efficient range queries to retrieve sequences of keys between specified boundaries.

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