Storing cybersecurity data at scale with SurrealDB

Calamu Technologies replaced a fragmented stack of DynamoDB, Neptune, Lambda, and Elasticsearch with SurrealDB, unifying access control, metadata, and telemetry for a distributed storage platform.

IndustryTechnology

OutcomeTech stack simplification from three databases to one

01 |KEY CHALLENGES

What they needed to solve

The technical and operational hurdles the team faced before adopting SurrealDB.

Fragmented architecture

A patchwork of services was expensive, slow, and difficult to manage.

Index overload

High-volume metadata patterns overloaded compound indexes and caused drift.

Millisecond response times

Critical workflows required consistent millisecond-scale lookups.

Deployment flexibility

Needed an embeddable database for on-prem and cloud with consistent access.

02 |SOLUTIONS

How SurrealDB helped

The architecture decisions and SurrealDB capabilities that addressed each challenge.

Unified multi-model architecture

Replaced multiple databases with one ACID-compliant engine for document and graph.

Flexible embedded deployment

Lightweight design enabled the same database in cloud and self-hosted environments.

High performance at scale

Delivered millisecond query latency over billions of records using range queries.

Operational efficiency

Roll-up tables and async inserts lowered infrastructure cost and sped delivery.

03 |RESULTS

The impact

Measurable outcomes delivered after moving to SurrealDB.

4 1

Cost & complexity savings

DynamoDB, Neptune, Lambda, and Elasticsearch consolidated into a single platform.

↑ SPEED

Ultra-fast performance

Backup manifest creation dropped to millisecond execution.

↑ UPTIME

Resilient architecture

Delivered consistent availability with fault-tolerant deployments.

↑ VISIBILITY

Built-in insight

Roll-up tables unlocked real-time observability into usage and costs.

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