Montycat brings Data Mesh principles to modern data infrastructure
A Rust-powered NoSQL database with ultra-low latency, hybrid in-memory and persistent storage, and built-in security — engineered for distributed systems that need flexibility without sacrificing performance.
Data Mesh gives teams ownership of their data as products
A decentralized architecture supported by self-serve infrastructure, purpose-built to replace monolithic data lakes and warehouses with domain-driven, federated data products.
Why Montycat
Every feature is designed to remove friction between your teams and your data — from the engine core to the developer experience.
Low Latency & High Throughput
Lightning-fast data processing and retrieval, up to 1,000,000 operations per second on a single node.
Unique Architecture
Seamlessly integrate and manage data across domains. Create keyspaces with flexible configurations and a unified view of your data landscape.
Built-in Security
TLS, RBAC, secrets management, and tamper detection — production-grade security out of the box.
Rust-Powered Core
Memory safety, no garbage collection pauses, and predictable performance for the data path that matters most.
Developer-Friendly APIs
Intuitive client libraries for Python, TypeScript, JavaScript, Dart, and Rust — no SQL injection by design.
Flexible Control
NoSQL flexibility with SQL-like capabilities: native foreign keys, optional strict schemas, and adaptable workloads.
Your data, your rules. Experience the power of flexibility.
Build Domains and Data Products with Confidence. No more monolithic data lakes.
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Montycat vs. PostgreSQL, MySQL, Redis & MongoDB
A snapshot of how Montycat's architecture, performance, and security posture stack up against the databases you already know.
| Montycat | PostgreSQL | MySQL | MS SQL Server | Redis | MongoDB | |
|---|---|---|---|---|---|---|
| Language Core | Rust (memory safe, no GC) | C | C++ | C/C++ | C (manual mem mgmt) | C++ |
| Storage Model | Hybrid: in-memory + persistent (LSM Tree) | Relational only | Relational only | Relational only | In-memory (optional persistence) | Doc store |
| Schema Support | Optional strict schemas | Rigid | Rigid | Rigid | None | Flexible |
| Data Mesh Ready | Built-in (domains) | No | No | No | No | No |
| Query / API Access | Structured API only (no SQL injection) | SQL | SQL | SQL (T-SQL) | Commands | MongoQL |
| Read Latency | Ultra-low | Higher (transactions) | Higher (transactions) | Higher (transactions) | Sub-ms | ~2–3ms |
| Write Latency | Very low + durable | Moderate–high | Moderate–high | Moderate–high | Very low (in-memory) | Moderate |
| Consistency | Strong local, eventual global (future PoS) | Strict ACID | Strict ACID | Strict ACID | Eventual | Configurable |
| Security Posture | Very Strong (TLS, RBAC, secrets, tamper detection) | Strong (manual setup) | Moderate (manual setup) | Moderate (manual setup) | Moderate | Moderate |
| Use Case Fit | Next-gen distributed systems | OLTP | OLTP | OLTP | Caching | Doc store |