Dystr

Ingest and connect to live data sources including sensor feeds, APIs, and telemetry streams without writing code. Automatically parse and normalize incoming data from multiple sources in real-time.

Build data processing pipelines and automation workflows using a visual interface without writing code. Chain together data transformations, filters, and conditional logic through drag-and-drop components.

Run engineering simulations on real-time or historical data to model system behavior, predict outcomes, or validate designs. Capabilities and supported simulation types are not clearly documented.

Apply transformations, aggregations, and filters to streaming or batch data using pre-built operators and custom logic. Clean, reshape, and enrich data in real-time without code.

Monitor data streams for anomalies or threshold violations and trigger alerts or notifications automatically. Route alerts to team members via email, webhook, or integrated communication channels.

Create real-time dashboards and visualizations of streaming data without coding. Display metrics, charts, and KPIs that update automatically as new data arrives.

Expose data processing workflows and simulation results as REST API endpoints without writing backend code. Allow external systems to query processed data or trigger workflows via HTTP requests.

Query, analyze, and run simulations against historical datasets stored in the platform. Compare past performance, identify trends, and validate models using archived data.

Combine and correlate data from multiple sources to identify relationships and dependencies. Join streams based on time windows, keys, or custom logic without writing code.

Schedule data processing workflows to run on fixed intervals, triggered by events, or based on data conditions. Manage dependencies between workflows and handle retries automatically.