12 个仓库
Tools for exporting and importing data via streaming protocols.
Distinguishing note: Focuses on Arrow-based streaming integration.
Explore 12 awesome GitHub repositories matching data & databases · Data Stream Integrations. Refine with filters or upvote what's useful.
DuckDB is an in-process analytical database engine designed to run directly within an application process. As a zero-dependency, embedded system, it provides enterprise-grade SQL data processing capabilities without the overhead of managing a dedicated database server. It is built to handle complex analytical and aggregation tasks by storing and retrieving information in columns, allowing for high-performance relational data manipulation. The engine distinguishes itself through a columnar vectorized execution model that maximizes CPU cache efficiency during query operations. It employs adapti
Enables high-performance data exchange by exporting query results as Arrow streams.
This project is a collection of educational resources and reference implementations for the Apache Flink stream processing framework. It provides a learning resource focused on mastering distributed stream processing through implementation guides, performance tuning tutorials, and practical examples. The repository features detailed walkthroughs for building real-time data pipelines using the DataStream and Table APIs. It includes specific integration examples for connecting Apache Flink with Kafka brokers and Elasticsearch indices, as well as reference implementations for real-time deduplica
Enables the integration of data flow between external storage systems and messaging queues across environments.
Open MCT is a web-based framework designed for visualizing telemetry data and monitoring the health of complex systems. It provides a centralized environment for ingesting, processing, and displaying real-time and historical data streams through customizable operator dashboards. The platform is built on a modular architecture that allows for the integration of external data sources and the addition of custom features through a plugin system. By utilizing a hierarchical object-graph model and a unified interface for time-series data, the framework ensures that information is consistently repre
Integrates diverse external telemetry streams into a centralized monitoring environment.
Redpanda is a distributed event streaming engine designed to serve as a high-performance, drop-in replacement for existing event-driven architectures. It provides a foundation for building and scaling applications that require reliable data movement, analytical querying, and strict operational compliance across both cloud and self-managed environments. The platform distinguishes itself through a shared-nothing architecture that utilizes thread-per-core execution and a non-blocking asynchronous input/output engine to maximize throughput. It maintains data consistency through a consensus-based
Connects external data sources and destinations to unify information flow across infrastructure.
Orleans is a .NET distributed actor framework designed for building scalable, cloud-native applications. It implements a virtual actor model where entities with stable identities manage their own state and lifecycle across a cluster of servers. The framework provides a distributed state management system with ACID transaction support and a distributed pub/sub streaming engine for real-time data processing. It distinguishes itself through location-transparent routing, automatic actor activation and deactivation, and elastic cluster scaling that redistributes workloads during node failures. Th
Implements tools for importing external data streams into internal actor types using data adapters.
Mage AI 是一个基于 Python 的数据流水线编排器和自托管数据集成开发环境。它旨在通过基于块的流水线设计和交互式笔记本界面来构建、调度和监控数据工作流。 该平台通过集成生成式 AI 功能脱颖而出,允许用户通过 API 连接大语言模型提供商,将人工智能纳入自动化数据流中。它还作为一个 Apache Spark 数据处理器,管理高性能分析和大规模数据处理所需的内核和基础设施。 该系统涵盖了广泛的数据工程功能,包括 ETL 工作流自动化、dbt 模型管理和数据流发现。它提供了通过 Git 进行版本控制集成、容器化部署以及基于角色的访问控制的工具,以管理跨开发和生产环境的流水线。监控通过系统性能遥测和流水线执行调试进行处理。
Identifies and lists available data streams from a source to determine datasets ready for synchronization.
Horizon is a realtime API server and RethinkDB backend designed to push database changes instantly to front-end clients. It utilizes a WebSocket data streaming API to synchronize data between the database and user interfaces without requiring manual polling. The project integrates an OAuth identity manager for verifying user identities through third-party providers and a role-based access control system to define granular permissions for viewing or modifying database documents. It is delivered as a containerized backend framework, allowing the server and its dependencies to be deployed as a p
Delivers instant data updates to front-end applications via a streaming API.
Streams 3D research data to and from a live USD stage in NVIDIA Omniverse for AI workflows.
X-Ray 是一个 Web 抓取框架和异步 Web 爬虫,旨在从网站中提取结构化数据。它作为一个 HTML 数据提取器,使用 CSS 样式选择器将原始页面内容转换为定义的模式。 该项目实现了一个能够执行 JavaScript 以渲染动态内容的无头浏览器爬虫。它通过广度优先爬取策略和自动分页发现来处理网站内容发现,以遍历多页结果集。 该框架使用并发限制的请求队列和请求速率控制来管理 Web 数据管线,以调节传出的网络调用。提取的结果通过基于流的数据持久化进行处理,以在不占用系统内存的情况下处理大数据集。
Exports extracted results via readable streams to ensure stability during long-running scraping tasks.
Inngest is a durable execution framework and event-driven automation engine designed to orchestrate background workflows. It enables developers to build resilient, stateful processes by memoizing function steps, ensuring that long-running tasks can automatically resume from the last successful operation after failures, timeouts, or infrastructure restarts. The platform distinguishes itself through its event-driven architecture, which uses a schema-validated bus to trigger functions and coordinate complex, multi-step logic. It employs an onion-model middleware approach for cross-cutting concer
Triggers rollback events for streamed data when a step fails, allowing clients to discard uncommitted updates.
dlt 是一个 Python 数据摄取工具和 ETL 流水线框架,旨在从不同来源获取数据并将其持久化到结构化目标中。它作为一个模式推断引擎,可自动检测数据类型并将嵌套的 JSON 结构扁平化为关系表,将数据从源端移动到数据湖、数据仓库或向量数据库。 该项目通过 AI 驱动的流水线生成脱颖而出,利用大语言模型为 REST API 构建提取代码和连接器。它还支持多模态向量存储和向量数据库的专门填充,以支持 AI 和机器学习应用。 该框架涵盖了广泛的功能,包括自动化模式演进、通过状态跟踪进行增量数据加载,以及通过强制执行数据契约进行数据质量验证。它提供了用于关系数据规范化、加载前后转换的工具,以及针对 SQL 数据库和云对象存储的多种目标适配器。 可观测性通过流水线执行仪表板、列血缘跟踪以及使用基于内容的哈希进行模式版本验证来处理。
Identifies and lists available data inputs by name or description to integrate new information streams.
BigchainDB 是一个区块链数据管理系统,旨在将大数据集存储在分布式账本上,同时保持传统数据库的查询性能。它为数据和数字资产提供不可变的记录存储,确保所有条目的可验证历史。 该项目将去中心化区块链结构与 NoSQL 数据库后端集成,以实现高效的索引和复杂的数据查找。它使用基于共识的状态复制模型和不可变事务日志来防止未经授权的记录篡改。 该系统通过 JSON-RPC API 和基于 HTTP 的数据流暴露账本状态和写入操作。这些接口允许程序化交互以及使用过滤器和查找来检索记录。
Delivers large sets of ledger data to clients using standard HTTP web requests for seamless integration.