Launch-ready data platform

Run your data stack anywhere. Replicate everywhere.

Stornamics gives teams full deployment flexibility while keeping data synchronized across regions, clouds, and on-premise environments.

  • Cloud, on-premise, or hybrid deployment
  • Cross-site replication with launch-ready products
  • Built for secure, enterprise-scale data movement

Product Release Snapshot

Track what is live and what is shipping next.

  • Core Databases

    CacheDB, TimeDB, and LogDB

    Released

    Serverless multi-tenant editions launched with replication-first architecture.

  • Security Layer

    Guardian

    Released

    Data security and privacy controls are available for launched product workflows.

  • Workflow Engine

    EdgeCompute

    In Progress

    Real-time event-driven processing is expanding with additional workflow templates.

  • Operational Scale

    Automated recovery and scaling

    Planned

    Roadmap investments focus on failover automation, retention policy tooling, and parallel query performance.

Explore the full roadmap

Why teams choose Stornamics

Purpose-built for high-trust data movement across modern infrastructure.

Anywhere-to-anywhere replication

Anywhere-to-anywhere replication

Keep cloud, on-premise, and hybrid environments synchronized without brittle custom pipelines.

Intelligent sync routing

Intelligent sync routing

Nodes replicate directly with each other or through the managed service based on your network topology.

Workflow and security controls

Workflow and security controls

EdgeCompute and Guardian extend launched products with real-time workflows and protection layers.

Built for real-world deployment complexity

From edge environments to multi-site enterprises, Stornamics adapts to how your teams operate.

Distributed cloud + on-prem data

Run production data across multiple offices and cloud regions without forcing one deployment model.

Logging and telemetry analytics

Store and query high-volume operational data with architecture built for growth and fast analysis.

Data analytics and ML pipelines

Synchronize datasets across environments so analytics and training workloads stay close to compute.

Developer productivity

Enable local and disconnected workflows while preserving reliable synchronization when connectivity returns.

Cross-institution collaboration

Share and protect research or operational data across organizations with traceable change history.