4 个仓库
Awesome GitHub RepositoriesShared-Nothing Processing Engines
Distributed processing models that execute tasks independently on worker nodes using network shuffle mechanisms.
Distinct from Shared-Nothing Architectures: Distinct from general shared-nothing architectures: focuses on the distributed processing and data shuffle execution model.
Explore 4 awesome GitHub repositories matching software engineering & architecture · Shared-Nothing Processing Engines. Refine with filters or upvote what's useful.
Awesome Shared-Nothing Processing Engines GitHub Repositories
用 AI 发现最棒的仓库。我们将通过 AI 为您搜索最匹配的仓库。
- prestodb/presto
prestodb/presto
16,711在 GitHub 上查看Presto is a distributed SQL query engine designed for high-performance analytical processing across heterogeneous data sources. It functions as a data federation platform and massively parallel processing engine, allowing users to execute interactive queries against diverse storage systems without requiring data migration. By mapping remote metadata and structures to a unified relational namespace, it enables seamless cross-platform analysis through a standard SQL interface. The engine distinguishes itself through a pluggable connector architecture and a shared-nothing distributed processing
Executes tasks independently on worker nodes by exchanging intermediate data through a high-performance network shuffle mechanism.
Javabig-datadatahadoop - apache/druid
apache/druid
14,020在 GitHub 上查看Apache Druid is a real-time analytics database and distributed columnar time-series store designed for sub-second analytical queries. It functions as a data platform featuring a distributed SQL query engine and a real-time data ingestion system for moving historical and streaming data from external sources. The system is distinguished by its ability to provide low-latency analytics under high concurrency to power operational dashboards. It implements a Kerberos-secured environment for user authentication and employs a shared-nothing cluster architecture to enable horizontal scaling. The plat
Employs a shared-nothing processing model to execute tasks independently on worker nodes, enabling horizontal scaling.
Javadruid - starrocks/starrocks
StarRocks/starrocks
11,789在 GitHub 上查看StarRocks is a distributed SQL OLAP database engine designed for real-time analytics and high-performance multi-dimensional analysis. It functions as a data lakehouse query engine that enables SQL execution across large datasets and external open table formats without requiring local data imports. The system employs a shared-nothing distributed architecture and utilizes the MySQL protocol to integrate with business intelligence tools. It maintains real-time data consistency through a primary key upsert model and accelerates query response times using vectorized execution and cost-based optimi
Employs a shared-nothing distributed processing model where each node manages its own local storage and memory.
Javaanalyticsbig-datacloudnative - databendlabs/databend
databendlabs/databend
9,351在 GitHub 上查看Databend is a cloud-native data warehouse and OLAP database designed for large-scale analytics. It functions as a SQL-compliant engine and serverless analytics platform that separates compute from storage to allow for independent scaling. The system integrates vector database capabilities, indexing high-dimensional embeddings to enable semantic, hybrid, and full-text searches across massive datasets. It further distinguishes itself through serverless compute management that automatically scales resources based on demand and shuts them down during idle periods. The platform covers a broad set
Distributes query processing across independent worker nodes to ensure high performance and availability.
Rustaibigdatacloud-native
