LevelDB | BestHub

DaTaobao Tech

Oct 19, 2022 · Databases

Overview of LSM‑Tree Architecture and Its Use in Modern Databases

LSM‑Tree stores writes in an in‑memory MemTable then flushes ordered SSTables to disk, using Bloom filters and indexes to speed reads, while periodic compactions merge files; modern systems such as LevelDB, HBase, and ClickHouse adopt this design to achieve high write throughput despite slower point and range queries and occasional compaction overhead.

Bloom FilterClickHouseDatabase

0 likes · 11 min read

Overview of LSM‑Tree Architecture and Its Use in Modern Databases

FunTester

Jan 4, 2022 · Databases

Practical Uses of LevelDB: Temporary Storage, Hidden Credential Management, Stateful Services, and Historical Data

This article introduces LevelDB, a Google‑open‑source key‑value store, and illustrates four practical use cases—temporary token storage, hidden credential management, stateful Java services, and lightweight historical data archiving, accompanied by Groovy/Java code examples for implementation.

Credential ManagementGroovyJava

0 likes · 6 min read

Practical Uses of LevelDB: Temporary Storage, Hidden Credential Management, Stateful Services, and Historical Data

FunTester

Dec 16, 2021 · Databases

Wrapping and Extending the LevelDB Java API with Custom Features

This article demonstrates how to encapsulate the native LevelDB Java API into a reusable class, adds support for integer values and Redis‑like operations such as increment, decrement, append, and cut, and provides complete code examples for the extended functionality.

Code ExampleDatabase WrapperJava

0 likes · 6 min read

Wrapping and Extending the LevelDB Java API with Custom Features

FunTester

Nov 16, 2021 · Databases

Using LevelDB with Java and Go: Basic API Operations

This article introduces LevelDB, a Google‑built key/value store, and demonstrates how to integrate it in Java and Go projects by showing dependency setup, basic operations such as opening, putting, getting, deleting, iterating, and closing the database, and explains the typical use cases and file layout.

APIDatabaseGo

0 likes · 8 min read

Using LevelDB with Java and Go: Basic API Operations

Python Programming Learning Circle

Sep 18, 2021 · Databases

Python Database Operations: SQLite, MySQL, LMDB, and LevelDB Tutorial

This tutorial walks through setting up Python 2.7 on Ubuntu, then demonstrates how to install, connect to, and perform CRUD operations with four different databases—SQLite, MySQL, LMDB, and LevelDB—showing complete example scripts and summarizing the key differences between relational and key‑value stores.

DatabaseLMDBLevelDB

0 likes · 8 min read

Python Database Operations: SQLite, MySQL, LMDB, and LevelDB Tutorial

Trip Tech Team

Aug 13, 2021 · Fundamentals

Why LevelDB Uses SkipLists: Memtable Mechanics and a Complete SkipListMap Implementation

This article explains the role and data structure of Memtable in LevelDB, introduces the probabilistic SkipList design, analyzes its time and space complexities, and provides a full Java implementation of a SkipListMap with code examples and a brief look at LevelDB's own SkipList implementation.

Data StructureJavaLevelDB

0 likes · 17 min read

Why LevelDB Uses SkipLists: Memtable Mechanics and a Complete SkipListMap Implementation

Trip Tech Team

Aug 12, 2021 · Databases

Unlocking HTAP: Inside TiDB, TiKV, RocksDB, and LevelDB Architecture

This article introduces TiDB’s hybrid transactional‑analytical processing capabilities, explains TiKV’s region‑based storage built on RocksDB, and provides a detailed overview of RocksDB and LevelDB architectures, including their data structures, write‑read flows, and key optimizations for modern distributed database systems.

Distributed DatabaseHTAPKV storage

0 likes · 16 min read

Unlocking HTAP: Inside TiDB, TiKV, RocksDB, and LevelDB Architecture

Tencent Cloud Developer

Dec 10, 2020 · Databases

Understanding LevelDB Architecture, Read/Write Flow, and Compaction Process

LevelDB stores data using an in‑memory Memtable that flushes to immutable tables and disk‑based SSTables, writes are logged then batched and applied through a writer queue, reads check Memtable, immutable Memtable, then SSTables, and background compactions merge tables to improve read performance and reclaim space.

CompactionDatabase InternalsLSM Tree

0 likes · 16 min read

Understanding LevelDB Architecture, Read/Write Flow, and Compaction Process

Tencent Cloud Developer

Sep 9, 2020 · Big Data

Tencent Game Marketing Deduplication Service: Technical Evolution from TDW to ClickHouse

Tencent’s game marketing analysis system “EAS” evolved from inefficient TDW HiveSQL jobs and file‑heavy real‑time pipelines to a scalable ClickHouse‑based deduplication service that processes hundreds of thousands of daily activity counts in sub‑second time, offering fast, reliable, and maintainable participant deduplication for massive marketing campaigns.

ClickHouseDeduplicationLevelDB

0 likes · 10 min read

Tencent Game Marketing Deduplication Service: Technical Evolution from TDW to ClickHouse

Architecture Digest

Feb 28, 2017 · Big Data

Architecture and Real‑Time Processing Design of Tencent Analytics (TA)

This article explains the architecture, real‑time computation framework, and storage solutions of Tencent Analytics, detailing how massive TB‑level web‑traffic data are collected via JavaScript, processed in memory‑centric streaming components, and stored using Redis and LevelDB to achieve second‑level updates.

LevelDBNoSQLReal-time Processing

0 likes · 13 min read

Architect

Mar 7, 2016 · Backend Development

Understanding Ceph PGLog: Format, Storage Mechanism, and Recovery Process

This article explains Ceph's PGLog structure, how it is serialized into transactions and stored in journals and LevelDB, and how the log participates in the recovery of degraded or failed placement groups during the peering process.

BackendCephDistributed Storage

0 likes · 15 min read

Understanding Ceph PGLog: Format, Storage Mechanism, and Recovery Process

Art of Distributed System Architecture Design

Sep 22, 2015 · Databases

An Overview of LevelDB: Design, Features, and Performance

LevelDB, created by Google Fellows Jeff Dean and Sanjay Ghemawat, is a high‑performance C++ key‑value library that provides persistent, ordered storage with snapshots, compression, and atomic batch operations, achieving up to 400,000 random writes and 60,000 random reads per second.

C++GoogleKey-Value Store

0 likes · 3 min read

An Overview of LevelDB: Design, Features, and Performance