5 个仓库
Mechanisms for performing database write operations on non-blocking background threads.
Distinct from Write Skew Mitigations: Focuses on non-blocking write execution for UI responsiveness, whereas write-skew mitigations focus on data integrity.
Explore 5 awesome GitHub repositories matching data & databases · Asynchronous Write Operations. Refine with filters or upvote what's useful.
This is a mobile object database and NoSQL local data store that replaces relational tables with a schema-based model. It functions as a reactive data store, using live object observations and change notifications to trigger automatic user interface refreshes. The system provides built-in mobile cloud data synchronization to keep local datasets consistent with a remote server across multiple devices. It also includes security features for encrypted local storage, protecting sensitive on-disk data using at-rest encryption keys and fine-grained access control. Broad capabilities include object
Supports modifying data on background threads to maintain a responsive main user interface.
Falcor is a JavaScript library that models remote data as a single virtual JSON graph, providing a path-based query engine for efficient client-side data retrieval and updates. It represents multiple remote data sources as a unified document where entities are accessed via globally unique identity paths. The system distinguishes itself by treating the remote data model as a virtual JSON resource, allowing the client to query specific paths without managing individual endpoints. It uses a reference-aware graph model to handle many-to-many relationships and prevents data duplication. Network ef
Updates values in a graph object at specified paths and returns the modified subset asynchronously.
Feast is an open-source feature store for machine learning that provides a central platform for defining, storing, and serving features across both training and inference workflows. It operates as a declarative system where feature definitions are written as code in Python files, synchronized to a central registry, and made available for low-latency online retrieval or point-in-time correct historical joins for training datasets. The project abstracts storage behind a pluggable architecture, allowing offline and online backends to be swapped without changing retrieval logic, and coordinates ma
Performs non-blocking batch writes using an async Redis client for use in async serving frameworks.
Booster 是一个 Android 应用构建优化器和字节码操作工具,旨在减小二进制体积、修复系统级崩溃并提升应用性能。它作为一个可扩展的构建流程插件,通过修改已编译的类文件和构建产物来注入稳定性修复和优化,而无需更改原始源代码。 该项目的差异化优势在于利用底层字节码操作来修补 OS 级 Bug,并在编译阶段管理线程池。它还提供了一个性能分析工具包,用于识别主线程阻塞操作并分析资源相关的稳定性问题。 该工具涵盖了广泛的包优化能力,包括 PNG 和 WebP 的图像压缩、冗余资源剔除以及资源索引优化。其他功能包括针对线程管理、异步偏好设置写入的性能调优,以及用于扫描构建产物以检测安全风险和瓶颈的静态分析。 该系统利用服务提供者接口(SPI)进行自定义插件集成,并可作为与主要构建环境解耦的独立应用程序执行。
Executes preference commits on asynchronous worker threads to prevent main thread blocking and UI freezes.
This project is a framework for implementing event sourcing and command query responsibility segregation within containerized microservices. It provides a structured approach to managing business state as a sequence of immutable events, ensuring a reliable audit trail and the ability to reconstruct system state at any point in time. The framework distinguishes itself by enforcing a clear separation between data modification and data retrieval paths. By utilizing event-driven data synchronization, it allows for the asynchronous updating of materialized views and read models, ensuring that quer
Performs non-blocking background updates to refresh query-optimized database views.