RedisJSON Outperforms MongoDB & ElasticSearch – Up to 200× Faster Writes

Overview

Recent official performance tests for RedisJSON (RedisSearch) claim it vastly outperforms other NoSQL solutions.

For isolated writes, RedisJSON is 5.4× faster than MongoDB and over 200× faster than ElasticSearch.

For isolated reads, RedisJSON is 12.7× faster than MongoDB and over 500× faster than ElasticSearch.

In mixed workloads, real‑time updates do not degrade RedisJSON’s search or read performance, unlike ElasticSearch.

RedisJSON supports roughly 50× more operations/second than MongoDB and 7× more than ElasticSearch.

RedisJSON latency is about 90× lower than MongoDB and 23.7× lower than ElasticSearch.

Latency and throughput remain stable at higher percentiles, and RedisJSON scales better as write ratios increase.

Query Engine

The development of reresearch and RedisJSON emphasizes performance, with each release delivering measurable improvements.

Version 2.2 loads and queries 1.7× faster than version 2.0, with better throughput and lower load latency.

2.1 Loading Optimization

Benchmark results from the New York City taxi dataset illustrate performance gains across releases.

2.2 Full‑Text Search Optimization

Indexing 5.9 million Wikipedia abstracts and running full‑text queries shows substantial improvements from v2.0 to v2.2 in write, read, and search latency.

Comparison with Other Frameworks

RedisJSON was benchmarked against MongoDB and ElasticSearch using the YCSB suite, covering CRUD operations plus a dedicated search workload.

3.1 Benchmark Setup

MongoDB 5.0.3

ElasticSearch 7.15

RedisJSON (RediSearch 2.2 + RedisJSON 2.0)

All tests ran on identical AWS m5d.8xlarge VMs with local SSDs, using a three‑node cluster (one client, three database servers) in a single availability zone.

3.2 100% Write Benchmark

RedisJSON ingests data 8.8× faster than ElasticSearch and 1.8× faster than MongoDB, while keeping sub‑millisecond latency; 99 % of requests complete under 1.5 ms.

RedisJSON uniquely updates its index on every write, unlike ElasticSearch’s near‑real‑time refresh model.

Overall, RedisJSON is 5.4× faster than MongoDB and over 200× faster than ElasticSearch for isolated writes.

3.3 100% Read Benchmark

RedisJSON delivers 15.8× higher read throughput than ElasticSearch and 2.8× higher than MongoDB, with sub‑millisecond latency across the board.

For isolated reads, RedisJSON is 12.7× faster than MongoDB and over 500× faster than ElasticSearch.

3.4 Mixed Read/Write/Search Benchmark

Mixed workloads (65 % search, 35 % read) show RedisJSON’s throughput remains stable as write ratios increase, while ElasticSearch’s throughput degrades sharply.

RedisJSON’s operations per second exceed MongoDB by 50.8× and ElasticSearch by 7×; latency is up to 91× lower than MongoDB and 23.7× lower than ElasticSearch.

3.5 Full Latency Analysis

3.5.1 MongoDB vs ElasticSearch vs RedisJSON

Across all latency percentiles, RedisJSON consistently achieves sub‑millisecond p99 latency (0.23 ms), far outperforming MongoDB (5.01 ms) and ElasticSearch (10.49 ms) for reads, and similarly low latency for writes.

3.5.2 ElasticSearch vs RedisJSON

At a sustained load of 6 K ops/sec, RedisJSON maintains a p99 read latency of 3 ms versus ElasticSearch’s 162 ms; for updates, RedisJSON’s p99 stays at 3 ms while ElasticSearch spikes to 167 ms.

Getting Started

To begin using RedisJSON, you can create a free Redis Cloud database in any region or run the RedisJSON Docker container. Updated documentation and client libraries for Node.js (node-redis), Java (Jedis), .NET (NRedisJSON, NRediSearch), and Python (redis‑py) simplify integration.