SAP HANA Nodes

Read from SAP HANA, change data with any statement, and bulk-load pipeline rows into HANA column tables.

Operations

Query · Execute · Write

Limits

50,000 rows or 40 MB per query

The SAP HANA nodes run the functions of an SAP HANA connection. Each node runs one function type.

Configuration Quick Reference

Field	What you choose	Details
Parameters	Connection, Function, Function Parameters, Timeout Override	Select the connection profile, function, configure function parameters with expression support, and optionally override timeout.
Settings	Description, Timeout (seconds), Retry on Timeout, Retry on Fail, On Error	Node description, maximum execution time, retry behavior on timeout or failure, and error handling strategy. All execution settings default to pipeline-level values.

Node Types

Node	Purpose	Common Use Cases
Query	Run a SELECT and return rows	Production orders, master data lookups, KPIs from HANA views
Execute	Run DML, DDL, UPSERT or CALL, return rows affected	Keeping a state table current, archiving, calling procedures
Write	Load pipeline rows into a table	Machine events, quality results, sensor history

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SAP HANA Query Node

SAP HANA Query Node

Run a SELECT and return its rows as structured data. Rows stream in up to the result limits; HANA decimals keep every digit, and SAP keys keep their leading zeros.

Supported Function Types:

Function Name	Purpose	Common Use Cases
Query	Run parameterized SELECT queries against SAP HANA	Order and material lookups, reporting, KPIs

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SAP HANA Execute Node

SAP HANA Execute Node

Run a statement that changes data or schema (INSERT, UPDATE, DELETE, UPSERT, MERGE, CREATE, ALTER, DROP or a procedure CALL) and return rowsAffected.

Supported Function Types:

Function Name	Purpose	Common Use Cases
Execute	Run any statement or procedure call	UPSERT … WITH PRIMARY KEY for exactly-once rows, cleanup, schema changes

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SAP HANA Write Node

SAP HANA Write Node

Load pipeline rows into a HANA table, matching fields to columns, in batches of Batch Size rows: one round trip and one transaction per batch, so a batch HANA refuses leaves none of its rows. With Create Table If Not Exists on, it creates a missing column table first; with Allow Schema Evolution on, it adds a column for a field the table lacks. See the Write Function for its fields.

Supported Function Types:

Function Name	Purpose	Common Use Cases
Write	Load structured data into an SAP HANA table	Event and sensor ingestion, auto-created tables

Output

Every SAP HANA node delivers its data under result, and execution facts (success, functionId, durationMs, timestamp) under _metadata:

Node	Expression	Description
Query	$node["Name"].result.rows	The result rows, one object per row keyed by column name as HANA reports it (unquoted names are upper case), up to the result limits: the 50,000-row cap and the 40 MB size budget by default. $node["Name"].result.rows[0].<column> reads a value
	$node["Name"]._metadata.truncated	true when the query hit a result limit and rows holds only what fit
	$node["Name"]._metadata.truncatedBy	Which limit cut the result: rows or bytes. Present only when truncated is true
	$node["Name"].result.rowCount	How many rows were delivered, the same as result.rows.length
Execute	$node["Name"].result.rowsAffected	Rows the statement affected, as HANA reports it
Write	$node["Name"].result.rowsInserted	Rows inserted across every batch of this execution

A Query also delivers $node["Name"]._metadata.driver (hdb), $node["Name"]._metadata.query (the SQL that ran), _metadata.truncated and, when a limit tripped, _metadata.truncatedBy. An Execute delivers _metadata.driver and _metadata.query. A Write delivers _metadata.driver, _metadata.table, _metadata.batchSize, _metadata.totalRows and _metadata.matchedColumns, plus _metadata.skippedFields or _metadata.schemaEvolution when they apply; when it created the table it delivers _metadata.tableCreated and _metadata.columns instead of matchedColumns.

Check truncated before you aggregate

A query stopped at the row limit returns a shorter rows array that looks exactly like a complete result. Branch on _metadata.truncated, or narrow the query with WHERE and LIMIT, rather than assuming the read was complete.