When You Need Speed—Redis Often Comes First

Redis is a well-known tool that helps speed up apps by storing frequently used data in memory. It’s often the go-to solution when you want to make something load faster. But what many teams don’t realize is that Redis also adds complexity:

• You have to run and manage a separate system.
• You need to write special code to use it efficiently.
• Keeping it working correctly takes time and effort.

For small projects or fast-moving teams at scale, that extra work can become a headache.

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The Typical Redis Setup: It Works, But...

First, you bolt a Redis server onto your stack—another container, another health check, another bill. Then every request tiptoes through boilerplate like this:

// Connect & retry logic lives elsewhere
const cached = await redis.get(`user:${id}`);
if { 
(cached) return JSON.parse(cached);      // cache HIT path
} 
else {
const fresh = await fetchFromAPI();            // cache miss path - fallback to origin
await redis.setEx(`user:${id}`, 3600, JSON.stringify(fresh)); // write-through
    return fresh;
}

That snippet looks innocent, but production needs serializers, key-versioning, metrics, and circuit-breakers—plus constant vigilance to keep your cache node patched and its memory from filling up. It works, absolutely, but the cognitive overhead piles on fast.

What Makes Harper Different?

Harper includes caching out of the box. Instead of bolting Redis onto your stack, you get a high-performance database with native caching built in—no separate service to deploy or extra code to maintain. Defining your data structure inherently keeps your data cached; you can even choose how it should be cached for more control by adding the expiration directive.

type ProductCache @table(expiration: 1800) @export {
  id: ID @primaryKey
  name: String
  price: Float
}

No extra work needed. Harper keeps hot data in memory and automatically refreshes stale entries. For situations where Harper is used as an additional caching layer (and not also doubling as the origin), you can define external data sources and easily set up a passive caching service similar to Redis. But you can also take this one step further with active caching and invalidation to ensure that cached data and source data don’t diverge.

Beyond caching, the above data schema also creates a REST endpoint with the @export command. That simple schema definition just set up a persistent datastore, an in-memory cache, and an API. Can Redis do that? 

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Real-World Use Cases: When Harper Is the Better Choice

Here are a few scenarios where Harper shines compared to Redis:

1. Global E-Commerce App

You want fast product lookups across the globe. Redis helps, but you need to sync it across regions. Harper’s built-in cache and global replication mean you get low-latency reads everywhere without the need for multiple systems.

Why Harper: One platform handles both your data and caching, and it scales globally.

2. Internal Dashboard or Admin Panel

These tools often don’t need millisecond speeds, but they do benefit from caching common queries. Harper gives you a quick and simple cache that you don’t need to babysit.

Why Harper: Less setup, and no need to justify spinning up Redis for a small gain.

3. Startups & MVPs

You’re building fast, and don’t want to deal with infrastructure. Harper gets you a data store and a cache with zero extra DevOps overhead.

Why Harper: Skip the Redis setup entirely and focus on building your product.

4. APIs That Pull From Other APIs

Need to store external API responses temporarily? Harper’s native cache lets you drop them right into a table, with automatic expiration.

Why Harper: Built-in TTLs, no JSON.stringify() gymnastics, and simple queries with SQL or GraphQL.

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Simple, Declarative Caching

With Harper, you don’t have to write custom code to manage the cache, learn a new query language, or add another server to monitor.

Instead, you just define your schema and go. Caching becomes part of your data model, not a separate concern.

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Looking Ahead: Redis Solves One Problem. Harper Solves Many.

Redis is great at what it does, but it only does one thing. Harper, on the other hand, gives you:

• SQL, NoSQL, and GraphQL queries
• Persistent Data Storage (including blob)
• Caching
• Edge replication
• Real-time Messaging
• Role-based access control

...all in one place.

So when your app grows, Harper is already ready.

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Ready to Give It a Try?

You can start with Harper in just a few minutes. First, install Harper. 

Once you have Harper installed and running, create a new project directory and initialize it with Harper's application template:

git clone https://github.com/HarperDB/application-template sample-app

cd sample-app

No Redis required.