Real-time Data Pipelines
Build pipelines that automatically react to streaming data changes
Overview
Traditional data pipelines require explicit orchestration at every step. When new data arrives, you manually trigger transformations, validate outputs, and propagate changes downstream. Slung eliminates this manual wiring by treating data sources as first-class entities with automatic dependency resolution and change propagation.
The Challenge
Building scalable data pipelines with traditional tools means managing complex DAGs, handling backpressure, implementing retry logic, and ensuring idempotency across stages. When a source changes unexpectedly, you need to manually trace dependencies and recompute affected stages. This creates brittle systems prone to data loss and inconsistency.
How Slung Helps
Slung models data sources and transformations as entities with relationships. When a source receives new data, the affected components are automatically marked dirty. Rules that depend on those components re-evaluate instantly. Changes cascade through your entire pipeline without explicit triggering, with built-in handling for ordering, idempotency, and consistency.
Key Benefits
Implicit Orchestration
No DAGs to manage. Relationships between data sources and transformations define execution automatically.
Real-time Propagation
Changes flow instantly through dependent stages with guaranteed consistency and no manual triggering.
Built-in Resilience
Automatic retry logic, idempotency guarantees, and ordering semantics prevent data loss and duplication.
Language Agnostic
Write transformations in any language. Compile to WebAssembly for universal deployment and execution.
Example: Analytics Pipeline
Imagine a real-time analytics pipeline ingesting user events. With Slung, you define rules that:
• Listen for new events on your data stream
• Automatically deduplicate and validate them
• Enrich with user context from your database
• Aggregate metrics that depend on enriched data
• Trigger alerts when thresholds are crossed
When a source changes or new data arrives, all dependent stages automatically re-evaluate. You write the logic once; Slung handles the orchestration.
Get Started
Explore the documentation to learn how to build your first pipeline, or view other use cases.
Slung lets you model your systems to handle complex scenarios without having to handle endless edge-cases:
Real-time Data Pipelines
Automatically react to streaming data changes and propagate updates across your pipeline without manual orchestration.
Event-driven Workflows
Execute workflows that adapt in real time based on changing facts and conditions across your system.
Distributed State Management
Maintain consistent global state across microservices with automatic propagation of changes.
Adaptive Business Logic
Build systems that automatically recalculate and adapt decisions when underlying data changes.