Elastic vs Redis

What Elastic is built to do

Full-text search

Indexes documents for relevance-ranked queries with analyzers and synonyms.

Log and metrics analytics

Ingests operational data and queries it through Kibana dashboards.

Self-hosted or managed

Runs on your own infrastructure or as a managed cloud deployment.

What Redis is built to do

In-Memory Storage

Store and retrieve data directly from RAM for maximum possible performance.

Persistence

Configure RDB or AOF to ensure your data survives a server restart.

Redis Sentinel

High availability solution for monitoring and automatic failover.

Geospatial Indexing

Store and query location data for building map-based applications.

Choose Elastic if

• Teams that want managed Elasticsearch without capacity planning — Serverless bills by VCU-hours and GB retained
• Search or logging workloads that need a supported cluster with 24/7 support and a 99.95% SLA (Platinum and up)
• Engineers who want to start self-managed for free and move to Cloud later on the same APIs

Skip Elastic if

• You need a flat monthly bill: Hosted 'as low as $99/month' assumes a 120 GB, 2-zone config and scales with usage
• Machine learning or cross-cluster replication is required — that starts at Platinum, from $131/month
• You just need basic search on a small app and cannot justify a managed cluster's floor price

Choose Redis if

• Running it yourself — the open-source version costs nothing at any scale
• Prototypes on the hosted service: the free Redis Cloud tier gives a 30 MB database
• Small production caches: Essentials starts at $5/month

Skip Redis if

• You need real capacity on the hosted plan — the free tier is 30 MB, which is a demo not a cache
• You need an SLA: the free tier is best-effort with community support only
• You need dedicated infrastructure or multi-region: Pro starts at a $200/month minimum

Elastic: pros & cons

• Extremely capable search and aggregation
• One stack for logs, metrics and search
• Large ecosystem and documentation
• Operationally demanding at scale
• Licensing changes have caused confusion
• Resource-hungry compared with focused tools

Redis: pros & cons

• Incredible Speed: Performs millions of operations per second with near-zero latency.
• Versatile Data Types: Supports strings, hashes, lists, sets, and sorted sets.
• Pub/Sub Support: Built-in messaging system for real-time application communication.
• Persistence Options: Can save data to disk while maintaining in-memory speed.
• RAM Limits: Your dataset size is limited by the amount of RAM available on your server.
• Complexity: Managing distributed clusters can be difficult for small teams.
• Data Loss Risk: If not configured correctly, an abrupt shutdown can lead to data loss.