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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.

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Node categories

Sources

Ingest from connections, tables, CDC, Iceberg, webhooks, and iterators.

Row transforms

Filter, sort, sample, and deduplicate rows.

Column transforms

Dates, windows, schema mapping, 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; build structured payloads for downstream systems.

Control flow

Branching, errors, loops, splits, and cross-pipeline triggers.

Data quality

Validate, profile, detect PII, generate test rows, and notify owners.

Advanced

SQL, scripts, notebooks, UDFs, streaming, ML, and geospatial operations.

Destinations

Write to warehouses, lakes, cloud storage, and webhooks.

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How to choose a node

1

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.
2

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.
3

Plan for failure

Add Error Handler or Notification nodes on critical paths so operational teams learn about issues before consumers do.

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Pipeline authoring resources

Pipeline canvas

Learn how to wire nodes, preview data, and debug runs.

Variables

Parameterize node settings for reuse across environments.