Tagged articles

8 articles

Page 1 of 1

Jan 8, 2026 · Big Data

How Gaode Maps Built a Real‑Time Lakehouse for Billion‑Scale Trajectory Data

This article details Gaode Maps' end‑to‑end lakehouse solution for massive, high‑frequency trajectory data, covering the challenges of real‑time visibility, query performance, and storage cost, and explaining how a hot‑warm‑cold tiering architecture built on Apache Flink, Paimon, StarRocks, Redis and Lindorm delivers millisecond‑level queries while cutting storage expenses.

Apache FlinkApache PaimonData Tiering

0 likes · 19 min read

How Gaode Maps Built a Real‑Time Lakehouse for Billion‑Scale Trajectory Data

StarRocks

Jan 7, 2026 · Big Data

How Gaode Maps Built a Real‑Time Lakehouse for Billion‑Scale Trajectory Data

This article details Gaode Maps' end‑to‑end lakehouse solution for handling high‑frequency, high‑volume trajectory data, covering the challenges of real‑time visibility, multi‑scenario queries, storage cost, and data silos, and describing the layered storage architecture, performance validation, and future expansion plans.

Apache FlinkData TieringLakehouse

0 likes · 21 min read

Baidu Intelligent Cloud Tech Hub

Sep 25, 2024 · Big Data

How Cold‑Hot Data Separation Boosts Cost Efficiency in Baidu Palo for Apache Doris

This article explains the principles, configuration steps, monitoring metrics, leader selection, data migration granularity, compaction, invalid data cleanup, and cache mechanisms of cold‑hot data separation in Baidu Intelligent Cloud's Palo for Apache Doris, illustrating how tiered storage reduces costs while maintaining query performance.

Apache DorisData TieringPalo

0 likes · 21 min read

How Cold‑Hot Data Separation Boosts Cost Efficiency in Baidu Palo for Apache Doris

Shopee Tech Team

Oct 8, 2021 · Databases

Cold‑Hot Storage Architecture and Practices in Shopee ClickHouse

Shopee ClickHouse implements a cold‑hot storage architecture by mounting JuiceFS‑backed S3 as a remote volume, using table‑level storage policies and TTL‑driven background moves to shift data from SSD to cold storage, achieving cost‑effective scalability, improved disk utilization, and validated performance despite operational challenges such as Redis memory pressure and small‑file handling.

Cold-Hot StorageData TieringDistributed OLAP

0 likes · 22 min read

Cold‑Hot Storage Architecture and Practices in Shopee ClickHouse

Tencent Cloud Developer

Dec 7, 2020 · Big Data

Searchable Snapshots in Elasticsearch 7.10: Features, Usage, and Future Outlook

Elasticsearch 7.10 adds searchable snapshots, letting users query indices stored directly in remote repositories such as S3 or COS, which halves storage costs, decouples storage from compute, supports manual mounting and ILM cold‑phase policies, and promises future full storage‑compute separation without local caching.

Big DataData TieringElasticsearch

0 likes · 12 min read

Searchable Snapshots in Elasticsearch 7.10: Features, Usage, and Future Outlook

21CTO

Oct 17, 2018 · Databases

Scaling Payment Systems: Sharding, Snowflake IDs, and High‑Availability

This article explains how to design a high‑throughput payment system using database sharding, Snowflake‑style globally unique order IDs, eventual consistency via message queues, high‑availability architectures, data tiering, and coarse‑fine traffic control to handle massive request spikes.

Data Tieringdatabaseeventual consistency

0 likes · 15 min read

Scaling Payment Systems: Sharding, Snowflake IDs, and High‑Availability

ITFLY8 Architecture Home

Oct 16, 2018 · Databases

Scaling Payment Systems: Sharding, Snowflake IDs, and High‑Availability Databases

This article explains how a high‑throughput payment platform uses database sharding by user ID, Snowflake‑style globally unique order IDs, asynchronous replication for eventual consistency, multi‑level data caching, and coarse‑fine traffic pipelines to achieve millions of requests per second with robust high‑availability.

Data Tieringhigh-availabilityorder ID

0 likes · 16 min read

Scaling Payment Systems: Sharding, Snowflake IDs, and High‑Availability Databases

dbaplus Community

Oct 25, 2017 · Big Data

Optimizing HDFS Storage with Heterogeneous Media, Erasure Coding, and Smart Storage Management

This article explains the challenges of growing data volumes, small files, and hot‑cold data in Hadoop HDFS, then details heterogeneous storage options, erasure‑coding techniques, and the open‑source SSM (Smart Storage Management) system that automates tiered storage based on data access patterns.

Data TieringHeterogeneous StorageSmart Storage Management

0 likes · 14 min read

Optimizing HDFS Storage with Heterogeneous Media, Erasure Coding, and Smart Storage Management