This article explains what Redis Modules are, lists the most popular official modules, and provides a step‑by‑step tutorial on installing Redis, setting up RedisJSON, and using its commands for creating, reading, updating, and deleting JSON data.
This article introduces Redis Stack’s RedisJSON module, explains its JSONPath syntax, details the full set of JSON commands for handling various data types, provides practical code examples, and highlights how RedisJSON enables Redis to function as a document, full‑text, and vector search database.
A comprehensive benchmark shows RedisJSON (RediSearch) dramatically outperforms MongoDB and ElasticSearch in isolated writes, isolated reads, mixed workloads, and latency, delivering up to 200‑plus times faster writes, over 500‑times faster reads, and significantly lower latency across all operation types.
This article presents a comprehensive design and performance‑optimization study for extracting up to 100 000 records from a pool of tens of millions, comparing multithreaded ClickHouse pagination, Elasticsearch scroll‑scan, ES + HBase, and RediSearch + RedisJSON solutions, and provides practical recommendations based on measured latency and throughput.
A comprehensive benchmark shows RedisJSON delivering dramatically higher throughput and lower latency than MongoDB and ElasticSearch across isolated writes, isolated reads, and mixed workloads, with up to 200‑fold faster writes and 500‑plus‑fold faster reads, while maintaining sub‑millisecond response times.
A comprehensive AWS benchmark reveals that RedisJSON dramatically outperforms MongoDB and ElasticSearch across isolated writes, isolated reads, mixed workloads, ops‑per‑second, and latency, maintaining sub‑millisecond response even under high update rates, while the other databases suffer significant slowdowns.
This article examines a business requirement to filter up to 100,000 items from a pool of tens of millions, presenting and evaluating four technical solutions—multithreaded ClickHouse pagination, Elasticsearch scroll‑scan, an ES‑HBase hybrid, and RediSearch + RedisJSON—along with performance data and implementation details.
This article examines a real‑world requirement to extract no more than 100 000 rows from a pool of tens of millions, comparing multithreaded ClickHouse pagination, Elasticsearch scroll‑scan deep paging, an ES‑HBase hybrid query, and a RediSearch‑RedisJSON approach, and presents performance measurements and practical conclusions.
A comprehensive performance benchmark shows RedisJSON delivering dramatically higher throughput and lower latency than MongoDB and ElasticSearch across isolated writes, isolated reads, and mixed workloads, highlighting its superior scalability and stability for modern data‑intensive applications.
This guide introduces RedisMod’s enhanced modules, shows how to install Redis with Docker, demonstrates native JSON storage using RedisJSON, walks through building and querying a full‑text search index with RediSearch—including Chinese support—and compares its performance against Elasticsearch.
The article presents a comprehensive performance benchmark of RedisJSON (with RediSearch) against MongoDB and ElasticSearch, showing RedisJSON’s superior write, read, and mixed‑workload throughput and latency across isolated and mixed scenarios, supported by detailed YCSB test results and analysis.
Benchmark tests reveal that RedisJSON, powered by RediSearch, dramatically outperforms MongoDB and ElasticSearch across isolated reads and writes, mixed workloads, and latency metrics, delivering up to 500‑fold speed gains, lower latency, and higher throughput, making it a compelling choice for modern data‑intensive applications.
The report presents a comprehensive performance benchmark of RedisJSON (RediSearch) against MongoDB and ElasticSearch, showing RedisJSON’s superior write, read, and mixed‑workload throughput and latency across isolated and hybrid scenarios, with detailed test methodology and analysis.
A comprehensive benchmark shows RedisJSON outperforms MongoDB and ElasticSearch by up to 12.7× on isolated reads, 5.4× on isolated writes, and delivers far lower latency and higher throughput across mixed workloads, thanks to its real‑time indexing and efficient query engine.
Recent benchmark tests show RedisJSON (with RediSearch) dramatically outperforms MongoDB and ElasticSearch, delivering up to 5.4‑times faster isolated writes, over 200‑times faster than ElasticSearch, 12.7‑times faster reads, and significantly lower latency and higher throughput across mixed workloads.
The report presents extensive YCSB‑based performance benchmarks showing that RedisJSON (with RediSearch) outperforms MongoDB and ElasticSearch by large margins in isolated writes, isolated reads, mixed workloads, and latency across a variety of operation mixes on identical AWS hardware.
Recent benchmark tests show that RedisJSON, powered by RediSearch, dramatically outperforms MongoDB and ElasticSearch in isolated writes, isolated reads, and mixed workloads, delivering up to 12.7× faster reads, 5.4× faster writes, and significantly lower latency across various operation types.
This article presents a detailed performance benchmark of RedisJSON (RediSearch) against MongoDB and ElasticSearch, showing RedisJSON’s superior throughput and latency across isolated writes, reads, and mixed workloads, supported by YCSB test results and extensive latency analysis.
