Nodes are the building blocks of every Planasonix pipeline. Each node performs one job: read data, reshape it, check quality, or write it somewhere else. You connect nodes with edges so outputs flow into inputs in a clear, reviewable graph. The library is grouped into sources, row transforms, column transforms, joins and unions, aggregation, parsers and builders, control flow, data quality, advanced code and engine integrations, and destinations. Browse by category below—each page lists node types, configuration fields you set in the inspector, and patterns that work well in production.Documentation Index
Fetch the complete documentation index at: https://docs.planasonix.com/llms.txt
Use this file to discover all available pages before exploring further.
Node categories
Sources
Ingest from connections, tables, CDC, Iceberg, webhooks, and iterators.
Row transforms
Filter, sort, sample, deduplicate, explode arrays, and Z-order sort rows.
Column transforms
Dates, windows, schema mapping, type inference, and guided data prep.
Joins and unions
Combine datasets with joins, fuzzy matching, and unions.
Aggregation
Summarize, pivot, and unpivot for analytics-ready shapes.
Parsers and builders
Parse CSV, JSON, and XML; flatten nested structures; build payloads for downstream systems.
Control flow
Branching, errors, loops, splits, and cross-pipeline triggers.
Data quality
Validate, profile, detect PII, detect anomalies, generate test rows, and notify owners.
Advanced
SQL, scripts, notebooks, UDFs, embeddings, streaming, ML, and geospatial operations.
Destinations
Write to warehouses, lakes, cloud storage, and webhooks.
How to choose a node
Start from the data shape
If data is not yet tabular, use a parser or source that emits rows. If it is already relational, jump to transforms or joins.
Prefer native nodes over scripts
Built-in nodes carry clearer metadata for lineage and optimization. Use Custom SQL or Python when you need logic that no single node expresses cleanly.
Pipeline authoring resources
Pipeline canvas
Learn how to wire nodes, preview data, and debug runs.
Variables
Parameterize node settings for reuse across environments.