RocksDB | BestHub

vivo Internet Technology

Dec 11, 2024 · Databases

RocksDB Memory Usage Analysis and Optimization: Troubleshooting Excessive Memory Consumption in Production

The article examines a production RocksDB memory‑usage problem where two instances consumed 59 GB on a 32‑CPU, 64‑GB server, identifies glibc ptmalloc’s unreclaimed free memory as the main cause, and shows that switching to jemalloc cuts usage by roughly 25 % while improving I/O and CPU efficiency.

Linux Memory ManagementMemory OptimizationRocksDB

0 likes · 11 min read

RocksDB Memory Usage Analysis and Optimization: Troubleshooting Excessive Memory Consumption in Production

360 Zhihui Cloud Developer

Sep 11, 2024 · Databases

Upgrade Pika to 3.5.x: Key New Features, Migration Guide & Rollback Tips

This article introduces Pika 3.5.x’s major enhancements—including a new sync mechanism, expanded Redis command support, RocksDB upgrades, BlobDB, containerization, observability tools, ACL and transaction support—while providing a step‑by‑step upgrade procedure, optional data synchronization, and two rollback strategies for safe migration.

Database upgradePikaRedis compatibility

0 likes · 17 min read

Upgrade Pika to 3.5.x: Key New Features, Migration Guide & Rollback Tips

AntData

Jun 26, 2024 · Databases

In‑Depth Analysis of Rockset’s Cloud‑Native Real‑Time Analytics Architecture

This article examines Rockset’s cloud‑native real‑time analytics database, detailing its document‑oriented data model, RocksDB‑Cloud storage engine, compute‑storage separation, sharding, converged indexing, query processing pipeline, and the implications of OpenAI’s recent acquisition for the broader database ecosystem.

RocksDBRocksetcloud native

0 likes · 14 min read

In‑Depth Analysis of Rockset’s Cloud‑Native Real‑Time Analytics Architecture

Bilibili Tech

Apr 9, 2024 · Big Data

Optimizing Flink State Performance with RocksDB KV Separation and BlobDB

In large‑scale Flink double‑stream joins, terabyte‑sized RocksDB state caused severe compaction latency and CPU spikes, but enabling RocksDB BlobDB KV‑separation (and an inner‑compaction patch) dramatically shrank SST files, reduced read/write latencies to sub‑millisecond levels, and cut CPU spikes by about half.

FlinkKV SeparationRocksDB

0 likes · 12 min read

Optimizing Flink State Performance with RocksDB KV Separation and BlobDB

Sohu Tech Products

Dec 13, 2023 · Databases

Fundamentals of RocksDB and Its Application in Vivo Message Push System

The article explains RocksDB’s LSM‑based architecture, column‑family isolation, and snapshot features, and shows how Vivo’s VPUSH mapping service uses these capabilities to store billions of registerId‑to‑ClientId mappings with high‑concurrency, low‑cost, fault‑tolerant performance across multiple replicated servers.

Column FamilyKey-Value StoreLSM Tree

0 likes · 24 min read

Fundamentals of RocksDB and Its Application in Vivo Message Push System

vivo Internet Technology

Dec 6, 2023 · Databases

RocksDB Fundamentals and Its Application in Vivo Message Push System

The article explains RocksDB’s LSM‑based architecture, column‑family isolation, and snapshot features, and shows how Vivo’s VPUSH MappingTransformServer uses these capabilities with C++ code to store billions of registerId‑to‑ClientId mappings across multiple replicated servers for high‑concurrency, low‑latency, and fast service expansion.

Column FamilyKey-Value StoreLSM Tree

0 likes · 25 min read

RocksDB Fundamentals and Its Application in Vivo Message Push System

Ctrip Technology

Nov 16, 2023 · Databases

Redis‑On‑Rocks (ROR): Architecture, Cold‑Hot Data Swapping, and Performance Evaluation

Redis‑On‑Rocks (ROR) extends the Redis codebase with RocksDB to provide cold‑hot data tiering, reducing memory costs by about two‑thirds while maintaining low latency and high throughput, and the article details its design, implementation, benchmarking against Redis‑on‑Flash, and production experience.

CacheColdHotStorageRedis

0 likes · 20 min read

Redis‑On‑Rocks (ROR): Architecture, Cold‑Hot Data Swapping, and Performance Evaluation

WeiLi Technology Team

Jun 2, 2023 · Big Data

Flink RocksDB State Backend: Practical Tuning Guide for Large Jobs

This article explains how to optimize Flink’s RocksDB state backend for large‑scale streaming jobs, covering state types, enabling latency tracking, incremental checkpoints, predefined options, and advanced memory and thread settings, with practical configuration examples and performance comparisons.

Big DataFlinkPerformance Tuning

0 likes · 16 min read

Flink RocksDB State Backend: Practical Tuning Guide for Large Jobs

Laravel Tech Community

Mar 21, 2023 · Databases

RocksDB Release Notes: Behavior Changes, Feature Removals, Build Changes, New Features, and Fixes

This article outlines the latest RocksDB release updates, including disabled checksum verification options, removed Lite and deprecated APIs, default shared library builds, new compression filter and MultiGetEntity APIs, and various bug fixes such as concurrency issues and async I/O error handling.

C++DatabaseKey-Value Store

0 likes · 4 min read

RocksDB Release Notes: Behavior Changes, Feature Removals, Build Changes, New Features, and Fixes

Architects' Tech Alliance

Oct 27, 2022 · Databases

Open-Channel SSD and Zoned Namespace (ZNS): Architecture, Benefits, and Performance with RocksDB and ZenFS

This article explains the principles of Open-Channel SSDs, their evolution into Zoned Namespace (ZNS) technology, compares performance of a commercial ZNS drive with traditional SSDs, and explores how databases like RocksDB and the ZenFS file system can exploit ZNS for higher efficiency and lower latency.

Flash Translation LayerOpen-Channel SSDRocksDB

0 likes · 16 min read

Open-Channel SSD and Zoned Namespace (ZNS): Architecture, Benefits, and Performance with RocksDB and ZenFS

Cognitive Technology Team

Oct 2, 2022 · Backend Development

Implementation Principles of RocketMQ Scheduled/Delayed Messages and Extending to Arbitrary Time Precision

This article explains how RocketMQ implements scheduled and delayed messages using fixed delay levels, the internal storage flow, code examples for setting delay levels, and advanced techniques such as RocksDB integration to achieve arbitrary time precision for delayed delivery.

Delayed MessageJavaMessage Queue

0 likes · 6 min read

Implementation Principles of RocketMQ Scheduled/Delayed Messages and Extending to Arbitrary Time Precision

JD Tech

Sep 6, 2022 · Big Data

Flink Streaming Job Tuning Guide: Memory Model, Network Stack, RocksDB, and More

This article presents a detailed guide for optimizing large‑scale Apache Flink streaming jobs on the JD Real‑Time Computing platform, covering TaskManager memory model tuning, network stack configuration, RocksDB state management, checkpoint strategies, and additional performance tips with practical examples and calculations.

Apache FlinkCheckpointPerformance Tuning

0 likes · 22 min read

Flink Streaming Job Tuning Guide: Memory Model, Network Stack, RocksDB, and More

58 Tech

Aug 11, 2022 · Backend Development

WLock: High‑Reliability, High‑Throughput Distributed Lock Service Based on WPaxos

WLock is an open‑source distributed lock service built on the WPaxos consensus algorithm and RocksDB storage, offering multiple lock types, flexible acquisition modes, high concurrency optimizations, and strong reliability and throughput for coordinating shared resources in distributed systems.

Distributed LockReliabilityRocksDB

0 likes · 12 min read

WLock: High‑Reliability, High‑Throughput Distributed Lock Service Based on WPaxos

IT Architects Alliance

Jul 31, 2022 · Backend Development

Design and Implementation of Delayed Messages in Distributed Message Queues

This article surveys common delayed‑message implementations—including external storage, RocksDB, Redis, and open‑source MQs like RocketMQ, Pulsar, and QMQ—detailing their architectures, advantages, disadvantages, and practical considerations for distributed asynchronous messaging systems.

Delayed MessagesMessage QueuePulsar

0 likes · 13 min read

Design and Implementation of Delayed Messages in Distributed Message Queues

Top Architect

Jul 31, 2022 · Backend Development

Design and Implementation of Delayed Message Queues in Distributed Systems

This article surveys common delayed‑message solutions in distributed asynchronous messaging, evaluates implementations based on external storage, databases, RocksDB, Redis, and open‑source MQs like RocketMQ, Pulsar and QMQ, and discusses their advantages, drawbacks, and practical design considerations.

Delayed MessagingMessage QueuePulsar

0 likes · 13 min read

Design and Implementation of Delayed Message Queues in Distributed Systems

DataFunTalk

Jul 4, 2022 · Big Data

Apache Ozone: Architecture, Advantages, and New Features Overcoming HDFS Limitations

This article explains the shortcomings of HDFS at large scale, describes the Federation and Scaling approaches, and details how Apache Ozone redesigns metadata storage, introduces container abstraction, object semantics, and new features such as optimized OM, streaming writes, erasure coding, and RocksDB consolidation to improve scalability and performance.

Apache OzoneErasure CodingHDFS

0 likes · 11 min read

Apache Ozone: Architecture, Advantages, and New Features Overcoming HDFS Limitations

Code Ape Tech Column

May 22, 2022 · Backend Development

Design and Implementation Strategies for Delayed Messages in Distributed Message Queues

This article reviews common delayed‑message implementation approaches—including external storage, RocksDB, Redis, and built‑in solutions in open‑source MQs like RocketMQ, Pulsar, and QMQ—detailing their architectures, advantages, drawbacks, and practical considerations for distributed systems.

Delayed MessagesMessage QueueRedis

0 likes · 13 min read

Design and Implementation Strategies for Delayed Messages in Distributed Message Queues

Aikesheng Open Source Community

May 19, 2022 · Databases

Performance Tuning of Pika KV Store: How max‑write‑buffer‑size Affects I/O and QPS

This article analyzes a real‑world migration from MongoDB to the open‑source Pika KV store, demonstrating how adjusting the max‑write‑buffer‑size parameter dramatically improves disk I/O characteristics and raises query‑per‑second throughput from 3 K to 40 K.

Performance TuningPikaRedis

0 likes · 9 min read

Performance Tuning of Pika KV Store: How max‑write‑buffer‑size Affects I/O and QPS

Bilibili Tech

May 17, 2022 · Cloud Computing

Bilibili Object Storage Service (BOSS) Design: Building a Large-Scale Distributed Storage System in 13 Days

In just 13 days Bilibili transformed a simple MySQL‑based S3 prototype into the BOSS distributed object storage system by separating metadata and data, adding an RPC abstraction layer, implementing two‑level sharding, switching to RocksDB, and deploying a three‑replica, multi‑zone high‑availability architecture.

Distributed StorageHigh AvailabilityReplication

0 likes · 15 min read

Bilibili Object Storage Service (BOSS) Design: Building a Large-Scale Distributed Storage System in 13 Days

Top Architect

May 13, 2022 · Backend Development

Design and Implementation of Delayed Message Queues in Distributed Systems

This article surveys common delayed message implementations—including external storage, RocksDB, Redis, and open‑source MQs like RocketMQ, Pulsar, and QMQ—analyzing their architectures, advantages, drawbacks, and practical considerations for building reliable distributed asynchronous messaging systems.

Delayed MessagesMessage QueuePulsar

0 likes · 13 min read