Deeply MongoDB-Native

Qarbine works directly with live MongoDB data and native MongoDB capabilities to deliver interactive operational views. MQL, the Document Model, Search, Vector Search, Voyage AI, Atlas services, and application context remain available throughout the operational experience.

MQL: Run native queries and aggregation pipelines directly, preserving MongoDB query semantics end to end.
Document Model: Keep nested documents, arrays, and business-object structures intact through downstream operational use.
Atlas Analytics Nodes: Direct appropriate Qarbine workloads to dedicated analytics nodes while separating them from primary application traffic.
Atlas Search + Vector Search: Use native full-text and vector retrieval directly within operational views and governed workflows.
Voyage AI: Use embeddings and reranking to improve retrieval quality and provide stronger context for RAG and inference.
Dynamic AI/RAG in Templates: Invoke AI prompts and inference while a view is processed so AI enrichment remains tied to live operational context.
Atlas Management API: “Query” Atlas objects and present consolidated operational and administrative views.
Embedded Operational Views + JavaScript SDK: Embed Qarbine views in applications with two-way interaction between the application and Qarbine.
Governed + Reusable Components: Manage optimized MongoDB retrieval and processing logic once and reuse it across operational views and the suite’s tools.
Qarbine Catalog on Atlas or Enterprise Advanced: Run the Qarbine catalog off the appliance to integrate more with your operations.

Three Key Distinctions

Work with Document Model Objects in Their Natural Form

MongoDB documents can contain different fields, nested objects, and arrays that reflect the application’s business domain. Qarbine templates work with those structures directly, using conditional logic and calculations without flattening them into tables. Even formulas such as value = #price * #numberOfShares reference document fields naturally. No disassembly required. No translation required. No flattening required.

Fully Use MongoDB’s Native Capabilities

Qarbine uses MongoDB’s native Node.js driver and MQL directly, including aggregation pipelines, Atlas Search, Vector Search, Analytics Nodes, and Voyage AI. There is no SQL-to-MQL translation or relational mapping layer. Developers can define optimized native queries once and reuse them across operational views.

Bring Source-of-Truth Operational Views into Applications

Applications can pass business objects or parameters directly into embedded Qarbine views while retaining the context of the user’s current task. Qarbine’s JavaScript SDK supports two-way interaction with the containing application. Teams can deliver detailed, interactive operational views from live MongoDB data without requiring a separate analytical store.

How to Get Started

Staying native to MongoDB preserves more of the value of the original database decision across operational use. Review the MongoDB tutorial to see Qarbine work directly with MongoDB data, MQL, Document Model objects, Search, Vector Search, and interactive operational views. Review the MongoDB related tutorial here.