PlanetScale vs Redis
Detailed comparison of PlanetScale and Redis to help you choose the right database tool in 2026.
Reviewed by the AI Tools Hub editorial team · Last updated February 2026
PlanetScale
Serverless MySQL database platform
The only MySQL platform with Git-like database branching and non-blocking schema changes, built on the same Vitess technology that scales YouTube, enabling teams to evolve database schemas safely without downtime.
Redis
In-memory data store and cache
Sub-millisecond in-memory data store with rich data structures that solve caching, queuing, real-time analytics, and pub/sub with single commands — the universal infrastructure layer behind fast applications.
Overview
PlanetScale
PlanetScale is a serverless MySQL-compatible database platform built on Vitess, the same open-source database clustering system that powers YouTube's database infrastructure at Google. Founded in 2018 by Jiten Vaidya and Sugu Sougoumarane — both former YouTube engineers who helped build and maintain Vitess — PlanetScale brought the horizontal scaling technology behind one of the world's largest websites to every developer through a managed cloud service. The platform differentiates itself with a unique branching workflow inspired by Git, non-blocking schema changes, and a serverless architecture that scales from zero to millions of queries per second. PlanetScale has raised over $100 million in funding and serves thousands of production databases, though the company made headlines in 2024 by removing its free tier, a controversial decision that pushed many hobby projects to alternatives.
Database Branching: Git for Your Schema
PlanetScale's most distinctive feature is database branching. Just as Git lets you create branches for code changes, PlanetScale lets you create branches for database schema changes. A development branch is a full copy of your database schema where you can experiment with ALTER TABLE statements, add indexes, or restructure tables without touching production. When ready, you open a Deploy Request (analogous to a Pull Request) that shows a diff of schema changes, allows team review with comments, and can be deployed to production with a single click. This branching model eliminates the fear of running migrations in production and enables schema changes to be reviewed with the same rigor as code changes.
Non-Blocking Schema Changes
Traditional MySQL databases lock tables during schema changes — adding a column or index to a large table can block reads and writes for minutes or hours, causing downtime. PlanetScale uses Vitess's Online DDL (based on gh-ost and pt-online-schema-change technology) to perform schema changes without locking tables or causing downtime. You can add columns, create indexes, modify column types, and restructure tables on multi-terabyte databases while the application continues to serve traffic at full speed. For teams that have experienced the pain of scheduling maintenance windows for database migrations, this feature alone justifies choosing PlanetScale.
Vitess-Powered Horizontal Scaling
Under the hood, PlanetScale runs Vitess, which shards MySQL across multiple nodes, distributes queries, and manages connection pooling at scale. This means PlanetScale databases can handle millions of queries per second by automatically distributing load across shards — capabilities that traditionally required a dedicated database infrastructure team to configure and maintain. For most users, sharding is transparent: you interact with what appears to be a single MySQL database while Vitess handles the complexity. PlanetScale also provides read replicas in multiple regions for low-latency global reads and automatic failover for high availability.
PlanetScale Boost and Insights
PlanetScale Boost is a built-in query caching layer that automatically caches the results of frequently executed queries, serving cached responses in under 1ms without any application code changes. You identify slow or frequently repeated queries through PlanetScale Insights — a query analytics dashboard that shows the most time-consuming queries, their frequency, rows examined, and latency percentiles — and enable Boost for specific query patterns. This combination of automatic query analysis and one-click caching provides performance optimization that typically requires a separate caching layer (Redis, Memcached) and significant application logic.
Pricing and Limitations
PlanetScale removed its free tier in April 2024, which was controversial and pushed many developers to alternatives like Supabase, Neon, and Turso. The Scaler plan starts at $39/month for 10 GB storage, 1 billion row reads, and 10 million row writes. Scaler Pro starts at $69/month with additional resources and features. Enterprise pricing is custom. The main limitations are the MySQL-only compatibility (no PostgreSQL option), the lack of a free tier for development and experimentation, the absence of foreign key constraint support in older Vitess configurations (though PlanetScale has added foreign key support more recently), and the serverless pricing model that can become expensive for write-heavy workloads. Additionally, PlanetScale is a managed service with no self-hosting option, meaning you are dependent on their infrastructure and pricing decisions.
Redis
Redis (Remote Dictionary Server) is the world's most popular in-memory data store, used by virtually every major tech company for caching, session management, real-time analytics, and message brokering. Created by Salvatore Sanfilippo in 2009, Redis processes millions of operations per second with sub-millisecond latency — performance that disk-based databases simply cannot match. It's the invisible infrastructure behind fast-loading pages, real-time leaderboards, rate limiters, and chat systems across the internet.
Beyond Simple Key-Value: Data Structures
What separates Redis from other key-value stores is its rich set of data structures. Beyond basic strings, Redis natively supports hashes, lists, sets, sorted sets, bitmaps, HyperLogLogs, streams, and geospatial indexes. A sorted set can power a real-time leaderboard with O(log N) inserts and range queries. A stream can serve as a lightweight message broker. HyperLogLogs count unique elements with 0.81% error using just 12KB of memory. These aren't add-ons — they're built into the core, each with optimized commands that make common patterns trivial to implement.
Redis Stack and Modules
Redis Stack extends the core with modules for JSON documents (RedisJSON), full-text search (RediSearch), time series data (RedisTimeSeries), probabilistic data structures (RedisBloom), and graph queries (RedisGraph, now deprecated). RediSearch is particularly powerful — it adds secondary indexing, full-text search with stemming and phonetic matching, and vector similarity search for AI/ML applications. These modules turn Redis from a pure cache into a multi-model database capable of handling diverse workloads in memory.
Persistence and Durability
Despite being in-memory, Redis offers two persistence mechanisms: RDB snapshots (point-in-time dumps at configurable intervals) and AOF (Append Only File, which logs every write operation). You can use both together for maximum durability. AOF with "everysec" fsync provides a good balance — you lose at most one second of data on crash. For use cases like caching where data loss is acceptable, you can disable persistence entirely for maximum performance. Redis Cluster provides replication across nodes, so data survives individual server failures.
Redis Cloud and Hosting Options
Redis Ltd. (the company, rebranded from Redis Labs) offers Redis Cloud, a fully managed service on AWS, Google Cloud, and Azure. The free tier provides 30MB — enough for development and small caches. Paid plans start at ~$5/month for 250MB. Alternatives include AWS ElastiCache, Azure Cache for Redis, Google Cloud Memorystore, and self-hosting. For most applications, managed Redis with 1-5GB of memory ($50-200/month) handles millions of daily requests comfortably.
Common Patterns
The most common Redis use cases follow well-established patterns. Caching: store database query results with TTL (time-to-live) to reduce load on your primary database. Session storage: keep user sessions in Redis for fast lookups across stateless application servers. Rate limiting: use INCR with EXPIRE to implement sliding window rate limiters. Pub/Sub: real-time message broadcasting for chat and notification systems. Job queues: use lists with BRPOP for reliable background job processing (libraries like Bull, Sidekiq, and Celery use Redis as their broker). Distributed locks: use SET with NX and EX for coordinating access across microservices.
Where Redis Falls Short
Redis stores everything in RAM, which is expensive. Storing 100GB in Redis costs 10-50x more than the same data in PostgreSQL on disk. This makes Redis unsuitable as a primary database for large datasets — it's a complement, not a replacement. Redis Cluster adds operational complexity with hash slots, resharding, and client-side routing. The single-threaded event loop (multi-threaded I/O was added in Redis 6) means CPU-intensive Lua scripts or large key operations can block all other clients. And the 2024 license change from BSD to dual RSALv2/SSPL has created uncertainty, spurring forks like Valkey (backed by the Linux Foundation).
Pros & Cons
PlanetScale
Pros
- ✓ Database branching with Deploy Requests brings Git-like workflow to schema changes — review, diff, and safely deploy migrations without downtime risk
- ✓ Non-blocking schema changes via Vitess Online DDL allow ALTER TABLE operations on production databases without locking tables or causing downtime
- ✓ Built on Vitess (YouTube's database technology) providing proven horizontal scaling to millions of queries per second
- ✓ PlanetScale Boost provides one-click query caching that serves cached results in under 1ms without application code changes
- ✓ PlanetScale Insights provides deep query analytics showing slow queries, row examination patterns, and latency percentiles for optimization
- ✓ MySQL compatibility means existing applications, ORMs, and tools (Prisma, Laravel, Django, Rails) work without modification
Cons
- ✗ No free tier since April 2024 — the $39/month minimum makes it expensive for hobby projects and learning compared to free alternatives like Supabase or Neon
- ✗ MySQL-only — no PostgreSQL support, which limits adoption among teams standardized on PostgreSQL
- ✗ Serverless pricing based on row reads and writes can become expensive and unpredictable for write-heavy workloads
- ✗ No self-hosting option — you are fully dependent on PlanetScale's infrastructure, pricing decisions, and continued operation
- ✗ Foreign key support was added late and comes with caveats — some teams still encounter limitations with complex relational schemas using Vitess sharding
Redis
Pros
- ✓ Sub-millisecond latency with millions of operations per second — the fastest data store available for caching and real-time workloads
- ✓ Rich data structures (sorted sets, streams, HyperLogLogs, geospatial) solve common problems with single commands instead of application code
- ✓ Extensive ecosystem with mature client libraries for every language and battle-tested job queue frameworks (Sidekiq, Bull, Celery)
- ✓ Redis Stack modules add full-text search, JSON support, and vector similarity search without a separate system
- ✓ Simple API with intuitive commands — GET, SET, INCR, ZADD — that developers learn in minutes
Cons
- ✗ Memory-bound storage makes it expensive for large datasets — 100GB of Redis costs 10-50x more than the same in PostgreSQL
- ✗ Not a primary database replacement for most workloads — best used alongside a disk-based database, not instead of one
- ✗ License changed from BSD to dual RSALv2/SSPL in 2024, creating uncertainty and spawning the Valkey fork
- ✗ Single-threaded command processing means CPU-heavy Lua scripts or large key scans can block all other clients
- ✗ Redis Cluster adds operational complexity with hash slots, resharding, and multi-key command limitations across slots
Feature Comparison
| Feature | PlanetScale | Redis |
|---|---|---|
| MySQL | ✓ | — |
| Branching | ✓ | — |
| Zero-downtime Schema | ✓ | — |
| Insights | ✓ | — |
| Boost Cache | ✓ | — |
| Key-Value Store | — | ✓ |
| Caching | — | ✓ |
| Pub/Sub | — | ✓ |
| Streams | — | ✓ |
| JSON Support | — | ✓ |
Integration Comparison
PlanetScale Integrations
Redis Integrations
Pricing Comparison
PlanetScale
Free / $39/mo Scaler
Redis
Free (OSS) / Cloud plans
Use Case Recommendations
Best uses for PlanetScale
SaaS Application with Frequent Schema Evolution
SaaS teams that ship database schema changes weekly use PlanetScale's branching workflow to test migrations safely. Developers create schema branches, open Deploy Requests for team review, and deploy to production without downtime. This is especially valuable for fast-moving startups where schema changes are a regular part of feature development.
High-Traffic Web Application Requiring Horizontal Scale
Applications handling millions of requests per day use PlanetScale's Vitess-powered sharding to scale beyond single-server MySQL limitations. The automatic connection pooling, read replicas, and horizontal scaling handle traffic spikes without manual intervention or database infrastructure expertise.
Global Application Needing Low-Latency Reads
Applications serving users worldwide deploy PlanetScale read replicas in multiple AWS regions. Users in Europe read from European replicas, users in Asia from Asian replicas, reducing query latency from hundreds of milliseconds to single-digit milliseconds for read-heavy pages and API endpoints.
E-Commerce Platform with Zero-Downtime Requirements
E-commerce platforms where any database downtime means lost revenue use PlanetScale's non-blocking schema changes and automatic failover. Adding indexes, columns, or restructuring tables happens transparently during peak traffic without scheduling maintenance windows or risking cart abandonment.
Best uses for Redis
Application Caching Layer
The most common Redis use case: cache database queries, API responses, and computed results with TTL expiration. A Redis cache in front of PostgreSQL or MongoDB typically reduces p95 latency by 10-100x and cuts database load by 60-90%.
Session Storage for Web Applications
Stateless application servers store user sessions in Redis, enabling horizontal scaling without sticky sessions. Redis's sub-millisecond lookups make session retrieval invisible to users, and TTL handles automatic session expiration.
Real-Time Leaderboards and Counters
Sorted sets power real-time leaderboards with O(log N) inserts and instant ranking queries. Gaming companies, social platforms, and analytics dashboards use Redis sorted sets to maintain millions of ranked entries updated in real time.
Background Job Queues and Message Brokering
Libraries like Sidekiq (Ruby), Bull/BullMQ (Node.js), and Celery (Python) use Redis as a reliable job queue backend. Redis Streams provide a Kafka-like log-based messaging system for event-driven microservice architectures at smaller scale.
Learning Curve
PlanetScale
Easy for developers already familiar with MySQL. PlanetScale presents as a standard MySQL database — you connect with any MySQL client, ORM, or driver and run standard SQL queries. The unique features (branching, Deploy Requests, Insights, Boost) are accessed through a clean web dashboard and CLI that are well-documented. The branching workflow may require a mindset shift for teams accustomed to running migrations directly against production. Understanding Vitess-specific behaviors (like sharding implications for certain query patterns) adds complexity for advanced use cases.
Redis
Low. Redis commands are intuitive (SET, GET, INCR, ZADD) and most developers learn the basics in an afternoon. Understanding when to use which data structure and designing effective key schemas takes more experience. Redis Cluster operations and production tuning require deeper knowledge.
FAQ
How does PlanetScale compare to Amazon RDS for MySQL?
Amazon RDS provides managed MySQL hosting with traditional infrastructure management — you choose instance sizes, manage storage scaling, and handle replication configuration manually. PlanetScale is serverless with automatic scaling, adds unique features like branching and non-blocking schema changes, and requires no infrastructure management. RDS is cheaper for stable, predictable workloads. PlanetScale is simpler to manage and better for teams that want the branching workflow and zero-downtime migrations. RDS gives you more control; PlanetScale gives you more developer experience features.
Why did PlanetScale remove the free tier?
PlanetScale removed its free tier (Hobby plan) in April 2024, citing the cost of supporting free databases that were not converting to paid plans. The decision was controversial, with many developers migrating to free alternatives like Supabase, Neon, and Turso. PlanetScale stated that the resources spent maintaining free-tier infrastructure were better directed toward improving the paid product. For developers who need a free MySQL database for learning or hobby projects, PlanetScale is no longer an option — alternatives like Railway, Aiven, or self-hosted MySQL fill that gap.
Should I use Redis as my primary database?
Generally no. While Redis supports persistence, its data size is limited by available RAM, which is expensive. Use Redis as a caching/session/queue layer alongside a primary database like PostgreSQL or MongoDB. The exception is if your dataset fits in memory (under ~50GB) and you need extreme performance — some applications use Redis as a primary store for real-time data like metrics, leaderboards, or rate limiting state.
What's the difference between Redis and Memcached?
Memcached is a simpler key-value cache that's slightly faster for basic string caching. Redis supports rich data structures (sorted sets, lists, streams, hashes), persistence, replication, Lua scripting, and pub/sub. For pure string caching, both work. For anything more complex — leaderboards, job queues, rate limiting, real-time analytics — Redis wins. Most teams choose Redis because it covers Memcached's use cases plus many more.
Which is cheaper, PlanetScale or Redis?
PlanetScale starts at Free / $39/mo Scaler, while Redis starts at Free (OSS) / Cloud plans. Consider which pricing model aligns better with your team size and usage patterns — per-seat pricing adds up differently than flat-rate plans.