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  • Cache vs. Database: Comparing Memcached and ScyllaDB
  • Cache vs. Database: Comparing Memcached and ScyllaDB

    An evergreen technical guide comparing Memcached caching and ScyllaDB NoSQL database, covering what each technology is, how they work, and why to choose one or both in modern architectures.
    3 February 2026 by
    Suraj Barman

    What is Caching?

    Caching stores frequently accessed data in fast‑access memory to reduce latency and load on primary storage systems.

    • Improves read performance
    • Reduces database query volume
    • Provides temporary data durability

    What is Memcached?

    Memcached is an open‑source, in‑memory key‑value store designed solely for caching.

    • Simple get/set API
    • Volatile storage (data lost on restart)
    • Horizontal scaling via sharding

    What is ScyllaDB?

    ScyllaDB is a high‑performance, distributed NoSQL database compatible with Apache Cassandra.

    • Persisted storage on SSDs
    • Automatic sharding and replication
    • Supports complex queries and secondary indexes

    How Do They Differ?

    Data Persistence

    Memcached stores data only in RAM; ScyllaDB writes to disk, providing durability.

    Data Model

    Memcached handles simple key‑value pairs; ScyllaDB supports tables, rows, and columns.

    Scalability

    Both scale horizontally, but ScyllaDB adds automatic load balancing and fault tolerance.

    Why Choose Memcached?

    • Ultra‑low latency for read‑heavy workloads
    • Simple deployment for transient data
    • Cost‑effective when data can be regenerated

    Why Choose ScyllaDB?

    • Need for durable, high‑throughput storage
    • Complex query requirements
    • Large data sets exceeding RAM capacity

    When to Combine Both?

    Many architectures use Memcached as a front‑line cache for hot data while persisting the source of truth in ScyllaDB.

    • Cache‑aside pattern
    • Write‑through or write‑behind strategies

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