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Level/levelupArchived

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Levelup

Levelup is a sorted key-value storage system that saves and retrieves data using byte arrays as keys and values. It provides a compatibility layer for Node.js and browsers that offers a unified interface for storage backends compliant with a specific abstract standard.

The project features an atomic batch write engine to execute multiple write and delete operations as a single unit for data consistency. It includes a range-based data streamer for reading keys and values as continuous sequences and an event-driven storage monitor to track asynchronous updates and state changes.

The system covers broader database primitives including range-based data deletion and backend engine abstraction to maintain a consistent command set across different runtime environments.

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Features

  • Key-Value - Provides a high-performance key-value storage system that uses raw byte arrays for platform-independent data retrieval.
  • Database Atomic Batches - Implements a mechanism to group multiple write and delete operations into a single atomic operation for data consistency.
  • LSM-Tree Batch Writes - Groups multiple mutations into a single atomic commit to ensure data consistency and reduce write amplification.
  • Cursor-Based Iteration - Implements a cursor mechanism for traversing sorted data sequences with support for bidirectional movement and pagination.
  • Lexicographical Range Reads - Allows the retrieval of all keys and values within a specific byte-sorted range using streaming and limits.
  • Atomic Transactions - Executes multiple data manipulation operations as a single atomic unit to ensure consistency.
  • Backend Compatibility Layers - Provides a compatibility layer for Node.js and browsers to interface with abstract-leveldown compliant backends.
  • Sorted - Enables the reading of keys and values as continuous sequences via range bounds and result limits.
  • Sorted Key-Value Maps - Provides a key-value store that maintains entries sorted by key to enable efficient range queries.
  • Storage Abstraction - Offers a middleware layer that provides a unified interface for interacting with different underlying storage backends.
  • Storage Backend Adapters - Provides an interface to interact with diverse storage engines using a consistent set of commands.
  • Storage Backend Adapters - Provides a unified interface that translates consistent commands into specific API calls for different storage backends.
  • Range Deletions - Allows the removal of specific data segments by defining upper and lower key boundaries.
  • Storage Event Notifications - Ships an event-driven monitor to track asynchronous updates and state changes within the data store.
  • Store Event Listeners - Implements a notification system using event listeners to react to asynchronous updates and state changes in the store.
  • Database Drivers - LevelDB interface.
  • Databases - LevelDB client.
4,072 stars·265 forks·JavaScript·MIT·21 views

Star history

Star history chart for level/levelupStar history chart for level/levelup

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

Frequently asked questions

What does level/levelup do?

Levelup is a sorted key-value storage system that saves and retrieves data using byte arrays as keys and values. It provides a compatibility layer for Node.js and browsers that offers a unified interface for storage backends compliant with a specific abstract standard.

What are the main features of level/levelup?

The main features of level/levelup are: Key-Value, Database Atomic Batches, LSM-Tree Batch Writes, Cursor-Based Iteration, Lexicographical Range Reads, Atomic Transactions, Backend Compatibility Layers, Sorted.

Which projects share features with level/levelup?

Projects with overlapping indexed features include: google/leveldb — LevelDB is an embedded database library and persistent storage engine that provides a sorted key-value store. It uses… apple/foundationdb — FoundationDB is an ACID-compliant distributed transactional key-value store. It functions as a scalable database… facebook/rocksdb — RocksDB is a high-performance, embeddable persistent key-value library and storage engine based on Log-Structured… rosedblabs/rosedb — RoseDB is a persistent key-value database and log-structured storage engine. It functions as a lightweight storage… spacejam/sled — Sled is an embedded key-value store and ACID-compliant database designed for high-performance data persistence. It… noderedis/node-redis — node-redis is a Node.js client and database driver for interacting with Redis key-value stores. It functions as a…

Projects sharing features with Levelup

These projects share indexed features with Levelup. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • google/leveldbgoogle avatar

    google/leveldb

    39,532View on GitHub↗

    LevelDB is an embedded database library and persistent storage engine that provides a sorted key-value store. It uses a log-structured merge-tree architecture to map byte arrays to values, running directly within a process to provide storage without the need for a separate server process. The system is distinguished by its use of custom comparison functions to define key ordering, enabling efficient range scans and sequenced lookups. It ensures data reliability through atomic batch execution, consistent snapshot generation, and log-based recovery after failures. The engine covers broad capab

    C++
    View on GitHub↗39,532
  • apple/foundationdbapple avatar

    apple/foundationdb

    16,446View on GitHub↗

    FoundationDB is an ACID-compliant distributed transactional key-value store. It functions as a scalable database engine that ensures strict serializability and data consistency across a cluster of servers using a shared-nothing architecture. The system is distinguished by its multi-region replication capabilities, allowing data to be synchronized across different datacenters for high availability and disaster recovery. It utilizes optimistic concurrency control to manage distributed transactions and employs a majority-based coordination system to maintain cluster state. The platform provides

    C++aciddistributed-databasefoundationdb
    View on GitHub↗16,446
  • facebook/rocksdbfacebook avatar

    facebook/rocksdb

    32,252View on GitHub↗

    RocksDB is a high-performance, embeddable persistent key-value library and storage engine based on Log-Structured Merge-trees. It is designed to provide durable storage for large-scale datasets, integrating directly into applications to manage data on flash and RAM-based hardware. The engine is distinguished by its focus on minimizing read and write amplification through multi-threaded compaction and custom memory allocators. It features specialized optimizations for flash storage, including support for zoned block devices, and provides the ability to extend store behavior via external plugin

    C++databasestorage-engine
    View on GitHub↗32,252
  • rosedblabs/rosedbrosedblabs avatar

    rosedblabs/rosedb

    4,878View on GitHub↗

    RoseDB is a persistent key-value database and log-structured storage engine. It functions as a lightweight storage system that utilizes a log-structured hash table and a Bitcask engine implementation to provide fast data retrieval and disk-backed persistence. The system operates as an atomic transaction engine, grouping multiple read and write operations into single units to maintain data consistency. It handles data through a key-value model that supports individual insertions, lookups, and deletions. The database provides capabilities for batch data processing and atomic updates. Additiona

    Godata-structuresdatabaseembedded
    View on GitHub↗4,878
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