Overview
This series explains how Pathway Live Data Framework maintains results as sources add, revise, remove, or deliver late data. It follows the graph from connectors and schemas through dynamic tables, transformations, and outputs; then shows how diffs, event time, delay, cutoff, and ASOF joins make revisions explicit. It connects those semantics to persistence, replay, worker coordination, scaling, monitoring, licensing, and live RAG indexing. The central value is one Python-described dataflow for batch and streaming relationships, bounded by replayable sources, sink contracts, operational limits, and the application's responsibility for answer quality, safety, and correctness.
Learning outcomes
- Pathway treats changing inputs as maintained state, letting affected results be revised rather than only appended or rebuilt.
- Its Python-described graph separates connectors, tables, transformations, runtime propagation, and sink-specific update handling.
- Batch and streaming can reuse processing logic, but streaming adds open-ended execution, revisions, and time and completion contracts.
- Persistence and replay support recovery, while live RAG answer quality still depends on parsing, retrieval, delivery, operations, and application evaluation.
Keywords
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PlansFAQ
What problem does Pathway Live Data Framework solve?
It keeps dataflow results aligned with sources that add, revise, remove, or deliver data late. It maintains table state and propagates affected changes rather than only appending events or rebuilding every snapshot.
How does Pathway handle updates to a live result?
It represents an update as removal of the previous row followed by insertion of its replacement, while additions and removals use the connector's change contract. Consumers can reconstruct current state, but append-only readers may mistake revisions for duplicates.
What is the difference between Pathway batch and streaming modes?
Batch processes finite input and can terminate; streaming remains active and revises results as new input arrives. The processing relationships can be reused, but completion, time, and output contracts differ.
Can Pathway live RAG guarantee correct answers?
No. Pathway can maintain a changing document index and retrieve updated context, but answer quality, citations, authorization, safety, and evaluation remain application responsibilities.