Redis 8.0 GA introduces major performance enhancements, adds AI‑focused vector and probabilistic data structures, expands native JSON support, improves the query engine with secondary indexes, and re‑embraces open source by offering an AGPLv3 licensing option.
Redis 8.0 GA introduces a suite of new data structures, AGPLv3 licensing, multithreaded query execution, horizontal scaling, and significant performance gains, positioning Redis as a more powerful in‑memory database for big‑data, AI, and real‑time applications.
Redis has launched an enhanced, multi‑threaded query engine that dramatically increases throughput and reduces latency for vector similarity searches, enabling vertical scaling and better support for real‑time RAG applications while maintaining sub‑10 ms response times.
This article explains DataFusion, a Rust‑written, Arrow‑based query engine that offers high performance, extensibility, and seamless integration with various data sources, detailing its architecture, execution model, Rust advantages, and practical usage examples for building modern data‑warehouse solutions.
This article introduces DataFusion, a high‑performance, Rust‑based query engine that leverages Apache Arrow’s columnar memory format to enable fast, extensible data processing across multiple storage formats and cloud sources, explains its architecture, execution model, and provides practical Rust code examples for custom extensions.
This article presents a comprehensive overview of TuGraph-DB, covering the historical development of graph query languages, the capabilities and future plans of the TuGraph 4.0 query engine, and the proposed architectural evolution to support multiple languages and storage back‑ends.
The article explains how Apache Arrow’s columnar, cross‑language in‑memory format enables high‑performance, interoperable data systems—replacing traditional row‑oriented databases—by supporting dynamic schemas, zero‑copy data exchange, efficient indexing, Acero‑based query execution, and Flight/ADBC connectivity, while offering practical guidance and highlighting challenges.
This article provides a comprehensive overview of TuGraph-DB's graph query language development, the capabilities of its 4.0 query engine, and the current and future architectural plans, including support for GQL, integration with GeaX, and optimization strategies for complex graph workloads.
This article presents Kuaishou's comprehensive data service system, covering its domain modeling, evolution from custom to unified services, the Octo query engine and data preparation platform architecture, the dual data API and analysis services, and future plans for intelligence and serverless high‑performance capabilities.
This article introduces the UData platform, explains its data‑integration architecture, details the StarRocks‑based query engine workflow from SQL parsing to distributed execution, and describes recent optimizations such as computation push‑down, support for JSF/HTTP/ClickHouse external tables, and a proxy‑based federated query framework.
The article details how Kuayue Group's big‑data center replaced Presto and ClickHouse with DorisDB, achieving sub‑second query latency, simplifying architecture, and enabling both online and real‑time OLAP analytics across millions of daily requests.
This article provides an in‑depth overview of Presto, covering its history, core principles, architectural components, query optimization techniques, resource management, tuning tips, data model, and case studies from companies like Didi and Youzan, offering practical guidance for deploying and operating the distributed SQL engine at scale.
This case study details how JD’s "Browse" UGC project evolved from rapid agile delivery to a performance bottleneck as data grew, and how introducing Elasticsearch, redesigning the query flow, and refactoring storage components restored fast, flexible searches for both front‑end and operations users.
The article provides a comprehensive overview of SQL‑on‑Hadoop query engines such as Hive, Impala, Presto and Spark SQL, comparing their runtime frameworks, core components, compilation steps, optimizer strategies, CPU/IO efficiency techniques, storage formats like ORC and Parquet, and resource management in a unified perspective.
This article details Ctrip's experience with the Presto distributed SQL engine, outlining the initial performance and stability issues, the comprehensive enhancements made in security, resource control, compatibility, and monitoring, and the multi‑stage upgrade plan that guides its future evolution.
This article introduces Hulu's in‑house OLAP engine Nesto, detailing its near‑real‑time data ingestion, nested data model, TB‑level storage using HBase and Parquet, MPP query execution, custom predicate library, and the overall architecture that enables sub‑second ad‑hoc queries for user analytics.
This article provides a comprehensive analysis of SQL‑on‑Hadoop architectures, comparing runtime‑framework‑based engines like Hive with MPP‑style engines such as Impala, detailing core components, compilation pipelines, optimizer strategies, CPU/IO performance tricks, columnar storage formats, and resource management in modern big‑data query platforms.
This article presents a non‑intrusive, high‑performance engine that adds secondary multi‑column indexes to Apache HBase, enabling efficient complex condition queries while preserving HBase's scalability, and details its principles, architecture, query API, index configuration, and practical trade‑offs.
