Pipedream data stores → n8n Data tables

In n8n, the closest thing to a Pipedream data store is a Data table, read and written with the Data Table node (what most people mean when they search for an n8n data store node). Pipedream data stores are a key-value store shared across workflows; n8n Data tables are small tables with columns, shared within a project. The catch is that Pipedream's export does not include data stores, so the records need their own backup. The backup runs as a Pipedream code step, so do it before workflows stop on March 31, 2027 (the data is deleted by April 30, 2027).

Concepts side by side

	Pipedream data store	n8n Data table	n8n workflow static data
Model	Key-value	Rows and columns	JSON object per workflow or node
Scope	Shared across workflows	Project	One workflow
Access	this.dataStore in Node.js, pd.inputs["data_store"] in Python, no-code actions	Data Table node, API, UI	$getWorkflowStaticData() in JavaScript Code node
TTL	Yes, per key	No	No
Size	Plan-dependent	200 MiB per instance by default	"should be small"
Saved in test runs	Yes	Yes	No

Sources: Pipedream data stores, n8n Data tables, n8n static data.

Step 1. Back up the records from Pipedream

There is no export button for data stores. Pipedream's docs include a sample action that posts records in chunks to an external endpoint; by default it deletes the keys it exported, so switch that option off for a copy. For small stores, a read-only code step is enough:

export default defineComponent({
  props: { store: { type: "data_store" } },
  async run() {
    const rows = [];
    for await (const [key, value] of this.store) rows.push({ key, value: JSON.stringify(value) });
    return rows;
  },
});

Select the data store in the prop, run the step once, and copy the result. Pipedream caps step exports and logs at 6 MB, so for larger stores post the rows to your own storage in batches instead.

Step 2. Create the Data table in n8n

1. In n8n, open the project and the Data tables tab.
2. Create a table, for example customers_seen, with columns key and value (both string).
3. Import the rows: the Data tables tab can create a table from a CSV, or you can insert rows with the Data Table node in a one-off workflow.

If your values are objects with a stable shape, use one column per field instead of a JSON string. Lookups and filters get easier.

Step 3. Replace data store calls

Pipedream (Node.js)	n8n
await this.store.get(key)	Data Table node → Get, filter key = ...
await this.store.set(key, value)	Data Table node → Upsert
await this.store.has(key)	Data Table node → If Row Exists / If Row Does Not Exist
await this.store.delete(key)	Data Table node → Delete
await this.store.keys()	Data Table node → Get (no filter)
set(key, value, { ttl })	No TTL: store an expires_at column and filter or delete on a schedule

The Data Table node's row operations are Delete, Get, If Row Exists, If Row Does Not Exist, Insert, Update and Upsert (node docs).

Because a Code node can't read a Data table directly, a code step that used a data store in the middle of its logic becomes three nodes: Data Table (read) → Code → Data Table (write).

When static data is fine

For a single workflow that keeps a cursor or "last seen ID", workflow static data is simpler:

const state = $getWorkflowStaticData('global');
const lastId = state.lastId ?? 0;
const fresh = $input.all().filter((item) => item.json.id > lastId);
if (fresh.length) state.lastId = Math.max(...fresh.map((item) => item.json.id));
return fresh;

Know the limits n8n documents: it's experimental, JavaScript only, not saved during manual test runs (the workflow has to be published and run by a trigger), saved only when the execution succeeds, and meant for small data.

What our converter does

To keep converted workflows running without manual edits, our converter maps data store calls in JavaScript code steps to workflow static data, and the report recommends a Data table for each store, with the import steps listed in the download. Data stores in Python steps are flagged red, because static data doesn't exist in n8n Python. The free report lists every data store your workflows use.

Next steps

• Back up everything else too: Pipedream data deletion checklist
• Code mapping: code steps to the n8n Code node
• Full guide: migrate Pipedream to n8n

Not affiliated with Pipedream or n8n.