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Awesome GitHub RepositoriesWrite-Ahead Logging

Persistence mechanisms that record data mutations to a log for durability and recovery.

Distinguishing note: Specific to log-based persistence for state recovery in distributed systems.

Explore 59 awesome GitHub repositories matching data & databases · Write-Ahead Logging. Refine with filters or upvote what's useful.

Awesome Write-Ahead Logging GitHub Repositories

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  • doocs/advanced-javadoocs 的头像

    doocs/advanced-java

    78,987在 GitHub 上查看↗

    This project is a comprehensive Java backend engineering guide and technical reference focused on high-concurrency design, distributed systems, and microservices architecture. It provides detailed strategies for decomposing monolithic applications, managing service discovery, and implementing the architectural patterns required for scalable backend environments. The repository distinguishes itself through an extensive collection of big data algorithmic references and database scaling strategies. It covers memory-efficient techniques for analyzing massive datasets, such as Top-K element extrac

    Provides mechanisms to record state-changing operations to a sequential disk log for durability and recovery.

    Javaadvanced-javadistributed-search-enginedistributed-systems
    在 GitHub 上查看↗78,987
  • google/leveldbgoogle 的头像

    google/leveldb

    39,152在 GitHub 上查看↗

    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

    Implements write-ahead logging to record every mutation for durability and crash recovery.

    C++
    在 GitHub 上查看↗39,152
  • qdrant/qdrantqdrant 的头像

    qdrant/qdrant

    32,372在 GitHub 上查看↗

    Qdrant is a high-performance vector similarity database designed to store, index, and search high-dimensional vectors alongside structured metadata. It functions as a distributed search engine that manages large-scale data clusters, providing low-latency retrieval and complex filtering capabilities. The system is built to serve as a specialized middleware layer, connecting machine learning pipelines and AI agents to persistent storage for intelligent information retrieval and recommendation tasks. The platform distinguishes itself through advanced retrieval techniques, including support for h

    Records all incoming data modifications in a sequential log to guarantee durability.

    Rustai-searchai-search-engineembeddings-similarity
    在 GitHub 上查看↗32,372
  • facebook/rocksdbfacebook 的头像

    facebook/rocksdb

    31,767在 GitHub 上查看↗

    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

    Records every mutation to a sequential on-disk log to ensure data durability and recovery after crashes.

    C++databasestorage-engine
    在 GitHub 上查看↗31,767
  • influxdb/influxdbinfluxdb 的头像

    influxdb/influxdb

    31,557在 GitHub 上查看↗

    InfluxDB is a high-performance time-series database designed for collecting, storing, and querying time-stamped metrics and event data. It functions as a columnar time-series store and a real-time analytics engine, providing a network-accessible interface for retrieving and analyzing temporal records. The system utilizes a specialized columnar storage format to support high ingestion rates and efficient data retrieval. It incorporates a programmable runtime for executing custom plugins and triggers, including integration for processing and transforming incoming data streams. The platform cov

    Records every incoming data point to a sequential append-only file to ensure durability.

    Rust
    在 GitHub 上查看↗31,557
  • pubkey/rxdbpubkey 的头像

    pubkey/rxdb

    23,048在 GitHub 上查看↗

    This project is a reactive, offline-first NoSQL database engine designed for JavaScript applications. It provides a robust framework for managing application state by synchronizing data across browsers, mobile devices, and server-side runtimes. By treating local storage as the primary source of truth, it enables applications to remain functional without network connectivity, automatically reconciling changes with remote backends once a connection is restored. The database distinguishes itself through a modular architecture that supports cross-environment synchronization and high-performance d

    Implements optimized write-ahead logging for high-performance read and write operations in IndexedDB.

    TypeScriptangularbrowser-databasecouchdb
    在 GitHub 上查看↗23,048
  • apache/incubator-rocketmqapache 的头像

    apache/incubator-rocketmq

    22,461在 GitHub 上查看↗

    RocketMQ is a distributed messaging and streaming platform designed for building event-driven applications. It serves as middleware to decouple services using publish-subscribe and request-reply patterns, and functions as a transactional messaging system that ensures atomicity by linking message delivery to local transaction outcomes. The platform includes specialized capabilities as a Kubernetes-native message broker for container orchestration environments and an MQTT broker for ingesting event data from mobile applications and hardware terminals. The system covers high-throughput data str

    Utilizes a sequential write-ahead log for high-throughput message persistence and durable state recovery.

    Java
    在 GitHub 上查看↗22,461
  • tursodatabase/tursotursodatabase 的头像

    tursodatabase/turso

    21,655在 GitHub 上查看↗

    Turso is a distributed SQL database platform that provides managed, edge-hosted SQLite instances. It functions as a serverless database provider, enabling the deployment of relational databases that synchronize data across multiple geographic regions to support high availability and performance. The platform distinguishes itself by utilizing a fork of SQLite as its core storage engine, which supports both local file storage and remote network-based replication. It employs an edge-optimized proxy to route queries through a global network, minimizing latency by connecting users to the nearest d

    Records database modifications to a sequential log to ensure crash recovery and data durability.

    Rustdatabaseembedded-databasesql
    在 GitHub 上查看↗21,655
  • valeriansaliou/sonicvaleriansaliou 的头像

    valeriansaliou/sonic

    21,249在 GitHub 上查看↗

    Sonic is a high-performance, lightweight search backend designed to provide real-time full-text search and autocomplete capabilities for applications. It functions as a persistent indexing server that maps text terms to object identifiers, allowing developers to integrate rapid search functionality without storing raw document content directly within the search engine. The system distinguishes itself through a specialized graph-based index that enables real-time word prediction and typo correction. Communication is handled via a custom, low-latency binary protocol over raw TCP sockets, which

    Ensures data durability and crash recovery by recording index modifications to a write-ahead log.

    Rustbackenddatabasegraph
    在 GitHub 上查看↗21,249
  • postgres/postgrespostgres 的头像

    postgres/postgres

    20,076在 GitHub 上查看↗

    PostgreSQL is an object-relational database management system designed for the persistent storage and retrieval of structured information. It functions as an ACID-compliant database server, utilizing standard query language protocols to maintain data consistency and reliability across large-scale application datasets. The system distinguishes itself through an extensible architecture that allows for the definition of custom data types, operators, and indexing methods. It employs multi-version concurrency control to enable simultaneous read and write operations without blocking, supported by a

    Records data modifications to a sequential log before applying changes to ensure durability during system failures.

    C
    在 GitHub 上查看↗20,076
  • pinojs/pinopinojs 的头像

    pinojs/pino

    17,941在 GitHub 上查看↗

    Pino is a high-performance logging library for Node.js applications designed to minimize overhead and prevent blocking the main event loop. It generates machine-readable logs using newline-delimited JSON, facilitating efficient ingestion and analysis by external monitoring and log aggregation platforms. The library distinguishes itself by offloading log processing and formatting to worker threads, ensuring that heavy logging tasks do not impact application responsiveness. It also provides a decoupled command-line utility that transforms structured production logs into human-readable text, sim

    Writes log data directly to the output stream to minimize latency and avoid asynchronous event queue overhead.

    JavaScriptfastjsonlogger
    在 GitHub 上查看↗17,941
  • questdb/questdbquestdb 的头像

    questdb/questdb

    17,062在 GitHub 上查看↗

    QuestDB is a high-performance, distributed time-series database designed for the ingestion, storage, and analysis of massive datasets. It functions as a real-time analytics platform that utilizes a columnar storage engine to optimize disk input and output, enabling efficient analytical scans and complex windowing operations on streaming data. The platform distinguishes itself through specialized capabilities for handling asynchronous time-series streams, including advanced join algorithms that align disparate data sets based on precise timestamp lookups. It supports high-volume ingestion thro

    Appends incoming data to a sequential log to ensure durability and crash recovery before merging into main storage.

    Javacapital-marketscppdatabase
    在 GitHub 上查看↗17,062
  • dgraph-io/badgerdgraph-io 的头像

    dgraph-io/badger

    15,666在 GitHub 上查看↗

    Badger is an embeddable key-value store written in Go that provides persistent data storage for byte keys and values. It is a persistent database that utilizes a tiered LSM tree storage model to optimize disk storage and retrieval efficiency. The system features an ACID transaction engine that ensures data integrity through serializable snapshot isolation and multi-version concurrency control. It also provides an encrypted key-value store with data-at-rest encryption and a managed encrypted key registry to secure stored information. The engine covers a broad set of capabilities including hig

    Uses a write-ahead log to record changes for durability and crash recovery.

    Godatabasedocument-databasego
    在 GitHub 上查看↗15,666
  • benbjohnson/litestreambenbjohnson 的头像

    benbjohnson/litestream

    13,240在 GitHub 上查看↗

    Litestream is a database backup utility that provides continuous, incremental replication for SQLite databases. It operates as a background process that monitors local database files and streams modifications to remote cloud storage, ensuring that off-site backups are maintained without manual intervention. The tool functions by intercepting the database file system layer to capture page-level changes and tailing the write-ahead log. This approach allows for real-time synchronization of transactions to various cloud object storage providers through a unified abstraction layer. Beyond continu

    Captures database modifications by continuously tailing the write-ahead log for real-time replication.

    Goreplications3sqlite
    在 GitHub 上查看↗13,240
  • mysql/mysql-servermysql 的头像

    mysql/mysql-server

    12,297在 GitHub 上查看↗

    MySQL Server is a relational database management system designed to organize and store structured information. It functions as a comprehensive SQL server platform that provides reliable transactional integrity and high-performance query execution for enterprise data management. The system distinguishes itself through a pluggable storage engine architecture that decouples logical query processing from physical data storage, allowing for specialized handling of diverse workloads. It maintains data consistency and high concurrency through multi-version concurrency control and write-ahead logging

    Records all data modifications to a persistent log file before applying changes to the database to guarantee durability during system failures.

    C++
    在 GitHub 上查看↗12,297
  • tporadowski/redistporadowski 的头像

    tporadowski/redis

    9,987在 GitHub 上查看↗

    Redis is a high-performance in-memory key-value store that functions as a distributed cache, message broker, and NoSQL database. It provides sub-millisecond read and write access to data stored in RAM and can operate as a vector database for indexing high-dimensional embeddings. The system supports a wide range of data storage and synchronization primitives, including the management of strings, hashes, lists, sets, and JSON documents. It enables real-time data operations through atomic transactions, hybrid persistence using snapshots and append-only logs, and high-availability configurations

    Implements a durable append-only file that records every write operation to ensure data recovery after failure.

    Credisredis-for-windowsredis-msi-installer
    在 GitHub 上查看↗9,987
  • sqlite/sqlitesqlite 的头像

    sqlite/sqlite

    9,909在 GitHub 上查看↗

    SQLite 是一个无服务器的关系型数据库引擎和 C 语言库,将数据存储在单个本地磁盘文件中。它作为嵌入式 SQL 数据库运行,直接集成到应用程序中,无需单独的服务器进程。 该引擎包含用于全文搜索索引和使用 R-Tree 结构进行空间数据查询的专门功能,适用于地理或几何坐标范围。 该系统提供了对 SQL 数据操作、数据库恢复与修复以及用于在数据库间同步修改的变更追踪的广泛支持。它还具有用于数据库管理和配置的终端界面。

    Employs write-ahead logging to ensure atomic commits and durability by recording changes before applying them to the main database.

    C
    在 GitHub 上查看↗9,909
  • apache/cassandraapache 的头像

    apache/cassandra

    9,778在 GitHub 上查看↗

    Cassandra is a distributed NoSQL database and wide-column store designed for high availability and linear scalability. It functions as a fault-tolerant distributed system that utilizes an LSM-tree storage engine to optimize write throughput and manage massive datasets. The system is a CQL-compliant database, using a structured query language to manage and retrieve tabular data stored across multiple nodes. It organizes information into rows and columns based on a flexible schema and primary keys. The project provides capabilities for horizontal database scaling, distributed data partitioning

    Implements a commit log to ensure all mutations are persisted to disk before memory updates for crash recovery.

    Javacassandradatabasejava
    在 GitHub 上查看↗9,778
  • mbdavid/litedbmbdavid 的头像

    mbdavid/LiteDB

    9,410在 GitHub 上查看↗

    LiteDB is a serverless, embedded NoSQL document database for .NET applications. It persists data into a single portable file, functioning as a BSON data store that resides within the application process rather than running as a separate server. The system is ACID compliant, utilizing write-ahead logging to ensure atomic, consistent, isolated, and durable transactions. It includes built-in encryption to provide secure local data storage and protect files on disk from unauthorized access. The project covers object-document mapping to convert classes into document formats, indexed search capabi

    Ensures ACID compliance and data durability by recording mutations to a write-ahead log.

    C#
    在 GitHub 上查看↗9,410
  • litedb-org/litedblitedb-org 的头像

    litedb-org/LiteDB

    9,409在 GitHub 上查看↗

    LiteDB is a serverless NoSQL document store and embedded database engine for .NET applications. It persists unstructured documents and binary data into a single standalone disk file, allowing the database to run within the application process rather than as a separate server. The system supports strongly typed queries through Language Integrated Query and allows the execution of standard SQL commands for data retrieval and transformation. It provides native mapping of plain classes into document formats and secures stored information via symmetric-key file encryption. The engine includes cap

    Employs write-ahead logging to record mutations and ensure atomic transactions and durability.

    C#databasedotnethacktoberfest
    在 GitHub 上查看↗9,409
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  3. Write-Ahead Logging

探索子标签

  • Checkpoint-Based Recovery SystemsRecovery mechanisms that use periodic checkpoints to bound the log replay range after a crash. **Distinct from Write-Ahead Logging:** Distinct from Write-Ahead Logging: combines WAL with checkpoint-based recovery for bounded crash recovery time.
  • Database WAL Streamings2 个子标签Continuous capture of database write-ahead logs to enable point-in-time recovery with near-zero data loss. **Distinct from Write-Ahead Logging:** Distinct from Write-Ahead Logging: focuses on continuous streaming of WAL data for recovery, not just log-based persistence.
  • Deployment JournalsPersistent logs specifically designed to track and resume multi-step software deployment processes. **Distinct from Write-Ahead Logging:** Distinct from general database Write-Ahead Logging: focuses on the orchestration state of deployments rather than data durability.
  • IndexedDB2 个子标签Persistence mechanisms that record data mutations to a log for durability and recovery. **Distinct from Write-Ahead Logging:** Distinct from general Write-Ahead Logging: specifically targets IndexedDB-based storage engines.
  • Log CompactionBackground processes that rebuild write-ahead logs to remove redundant operations and reclaim disk space. **Distinct from Write-Ahead Logging:** Focuses on the optimization and shrinkage of the log rather than the initial recording of mutations.
  • Log RetrievalCapabilities for fetching specific archived log segments from storage for recovery purposes. **Distinct from Write-Ahead Logging:** Distinct from general Write-Ahead Logging: focuses specifically on the retrieval of archived segments rather than the mechanism of recording mutations.
  • Log Sequence TrackingTracking of write-ahead log identifiers to ensure a continuous chain for point-in-time recovery. **Distinct from Write-Ahead Logging:** Focuses on the indexing and sequencing of logs for recovery rather than the persistence mechanism itself.
  • Log Streaming1 个子标签Mechanisms for streaming log files from database primaries to remote storage in real-time. **Distinct from Write-Ahead Logging:** Distinct from general Write-Ahead Logging: focuses on the transport and streaming process to cloud storage.
  • Log-Free Persistence StrategiesTechniques for writing data directly to disk without a commit log to reduce write amplification. **Distinct from Write-Ahead Logging:** Distinct from Write-Ahead Logging: focuses on avoiding a log entirely, not on log-based recovery.
  • Log-Structured Storage EnginesStorage engines that utilize a write-ahead log and page cache to optimize write throughput. **Distinct from Write-Ahead Logging:** Distinct from Write-Ahead Logging: refers to the entire storage engine architecture, not just the logging mechanism.
  • Row-Level LoggingWrite-ahead logging that records individual row changes as logical deltas instead of physical page images. **Distinct from Write-Ahead Logging:** Specifically covers logical row-level logging as opposed to general physical write-ahead logging
  • Synchronous Log WritersMechanisms that write log data directly to output streams to minimize latency. **Distinct from Write-Ahead Logging:** Distinct from Write-Ahead Logging: focuses on synchronous stream output for performance rather than durability-focused persistence.
  • TSDB Write-Ahead Logging with Block Flushing1 个子标签Appending incoming samples to a per-tenant TSDB backed by a write-ahead log, then periodically uploading blocks to object storage. **Distinct from Write-Ahead Logging:** Distinct from Write-Ahead Logging: combines WAL with periodic TSDB block flushing to object storage, not just log-based persistence.
  • WAL ArchiversUtilities specifically designed to capture and upload write-ahead logs to remote storage. **Distinct from Write-Ahead Logging:** Focuses on the external archival of logs rather than the internal mechanism of writing them.
  • WAL ArchivingContinuously pushing write-ahead log files to a secure repository and pruning expired archives. **Distinct from Write-Ahead Logging:** Focuses on the archiving and pruning process rather than the internal logging mechanism itself.
  • WAL Volume IsolationPhysical separation of write-ahead logs from primary data directories using distinct storage volumes. **Distinct from Write-Ahead Logging:** Focuses on the storage isolation of the WAL rather than the logging mechanism itself.
  • Write IO OptimizationsTechniques to minimize physical disk operations during data mutation. **Distinct from Write-Ahead Logging:** Focuses on reducing overall IO overhead via logical logs, not just the persistence mechanism of WAL.