Technology Stack

NoSQL & In-Memory Data

We reach for a dedicated data store when the access pattern calls for it — not because NoSQL is trendy.

DynamoDB

Primary key and Global Secondary Index (GSI) design for high-throughput, low-latency access patterns — designed and built as part of SPAM Escudo’s serverless architecture.

Redis & Valkey

In-memory caching layers on AWS for latency-sensitive workloads — running alongside Cerberus ID’s versioned Lambda scoring service.

JSON in Commercial SQL

Native JSON data types in MySQL, Oracle, and other commercial SQL engines, for semi-structured data that doesn’t justify standing up a separate NoSQL store.

The right store depends on the access pattern: a dedicated key-value store when throughput and predictable latency matter (DynamoDB), an in-memory layer when raw speed is the constraint (Redis/Valkey), or a JSON column when the data is mostly relational with a semi-structured edge. Get in touch to talk through which fits your workload.