RedisJSON vs MongoDB & ElasticSearch: 200× Faster Writes & 500× Faster Reads

Overview

Recent official testing reports demonstrate that RedisJSON (RediSearch) dramatically outperforms other NoSQL solutions. Key conclusions:

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

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

In mixed‑workload scenarios, real‑time updates do not degrade RedisJSON’s search or read performance, whereas ElasticSearch’s performance drops. RedisJSON supports roughly 50× more operations per second than MongoDB and 7× more than ElasticSearch, with latency about 90× lower than MongoDB and 23.7× lower than ElasticSearch.

Query Engine

The development of reresearch and RedisJSON emphasizes performance; each release includes analysis tools for performance profiling. Version 2.2 improves load and query performance by 1.7× over version 2.0, with better throughput and lower data‑load latency.

2.1 Load Optimization

The following figures show results of the New York City taxi benchmark.

Each new reresearch version brings substantial performance gains.

2.2 Full‑Text Search Optimization

To evaluate search performance, 5.9 million Wikipedia abstracts were indexed and a full‑text search query panel was run. The migration from v2.0 to v2.2 yields large improvements in write, read, and search latency, increasing overall Search and JSON throughput.

Comparison with Other Frameworks

RedisJSON was compared against MongoDB and ElasticSearch using the YCSB benchmark suite, measuring latency and throughput under various workloads, including added search operations.

3.1 Benchmark Setup

Software versions used:

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, forming a three‑node cluster (one client, three database servers) in a single availability zone.

3.2 100% Write Benchmark

RedisJSON’s ingestion speed is 8.8× faster than ElasticSearch and 1.8× faster than MongoDB, while maintaining sub‑millisecond latency; 99 % of Redis requests complete in under 1.5 ms. RedisJSON uniquely updates its index on every write, unlike ElasticSearch’s near‑real‑time (NRT) indexing.

3.3 100% Read Benchmark

RedisJSON reads 15.8× more operations than ElasticSearch and 2.8× more than MongoDB, keeping sub‑millisecond latency across the entire latency range.

3.4 Mixed Read/Write/Search Benchmark

A realistic mixed workload (65 % search, 35 % read) shows RedisJSON’s throughput remains stable as write ratio increases, while ElasticSearch’s throughput drops sharply. RedisJSON maintains sub‑millisecond latency even with 10 % writes added to the mix.

3.5 Full Latency Analysis

Across all operation types, RedisJSON consistently exhibits the lowest latency. In the p99 percentile, RedisJSON records 0.23 ms, compared with 5.01 ms for MongoDB and 10.49 ms for ElasticSearch. Both write and read latencies remain sub‑millisecond for RedisJSON, whereas ElasticSearch shows high tail latency (>10 ms) due to GC and cache misses.

Overall, RedisJSON delivers up to 50.8× higher ops/sec than MongoDB and 7× higher than ElasticSearch in mixed workloads, with latency reductions of up to 91× versus MongoDB and 23.7× versus ElasticSearch.