Using Data Stores

In Node.js (JavaScript) code steps, you can also store and retrieve data within code steps without connecting a 3rd party database. Add data stores to steps as props. By adding the store as a prop, it’s available under this. For example, you can define a data store as a dataStore prop, and reference it at this.dataStore:

export default defineComponent({
  props: {
    // Define that the "dataStore" variable in our component is a data store
    dataStore: { type: "data_store" },
  },
  async run({ steps, $ }) {
    // Now we can access the data store at "this.dataStore"
    await this.dataStore.get("email");
  },
});

props injects variables into this. See how we declared the dataStore prop in the props object, and then accessed it at this.dataStore in the run method.

All data store operations are asynchronous, so must be awaited.

Using the data store

Once you’ve defined a data store prop for your component, then you’ll be able to create a new data store or use an existing one from your account.

Saving data

Data Stores are key-value stores. Save data within a Data Store using the this.dataStore.set method. The first argument is the key where the data should be held, and the second argument is the value assigned to that key.

export default defineComponent({
  props: {
    dataStore: { type: "data_store" },
  },
  async run({ steps, $ }) {
    // Store a timestamp each time this step is executed in the workflow
    await this.dataStore.set("lastRanAt", new Date());
  },
});

Setting expiration (TTL) for records

You can set an expiration time for a record by passing a TTL (Time-To-Live) option as the third argument to the set method. The TTL value is specified in seconds:

export default defineComponent({
  props: {
    dataStore: { type: "data_store" },
  },
  async run({ steps, $ }) {
    // Store a temporary value that will expire after 1 hour (3600 seconds)
    await this.dataStore.set("temporaryToken", "abc123", { ttl: 3600 });
 
    // Store a value that will expire after 1 day
    await this.dataStore.set("dailyMetric", 42, { ttl: 86400 });
  },
});

When the TTL period elapses, the record will be automatically deleted from the data store.

Updating TTL for existing records

You can update the TTL for an existing record using the setTtl method:

export default defineComponent({
  props: {
    dataStore: { type: "data_store" },
  },
  async run({ steps, $ }) {
    // Update an existing record to expire after 30 minutes
    await this.dataStore.setTtl("temporaryToken", 1800);
 
    // Remove expiration from a record
    await this.dataStore.setTtl("temporaryToken", null);
  },
});

This is useful for extending the lifetime of temporary data or removing expiration from records that should now be permanent.

Retrieving keys

Fetch all the keys in a given Data Store using the keys method:

export default defineComponent({
  props: {
    dataStore: { type: "data_store" },
  },
  async run({ steps, $ }) {
    // Return a list of all the keys in a given Data Store
    return await this.dataStore.keys();
  },
});

Checking for the existence of specific keys

If you need to check whether a specific key exists in a Data Store, you can pass the key to the has method to get back a true or false:

export default defineComponent({
  props: {
    dataStore: { type: "data_store" },
  },
  async run({ steps, $ }) {
    // Check if a specific key exists in your Data Store
    return await this.dataStore.has("lastRanAt");
  },
});

Retrieving data

You can retrieve data with the Data Store using the get method. Pass the key to the get method to retrieve the content that was stored there with set.

export default defineComponent({
  props: {
    dataStore: { type: "data_store" },
  },
  async run({ steps, $ }) {
    // Check if the lastRanAt key exists
    const lastRanAt = await this.dataStore.get("lastRanAt");
  },
});

Retrieving all records

Use an async iterator to efficiently retrieve all records or keys in your data store:

export default defineComponent({
  props: {
    dataStore: { type: "data_store" },
  },
  async run({ steps, $ }) {
    const records = {};
    for await (const [k,v] of this.dataStore) {
      records[k] = v;
    }
    return records;
  },
});

Deleting or updating values within a record

To delete or update the value of an individual record, use the set method for an existing key and pass either the new value or '' as the second argument to remove the value but retain the key.

export default defineComponent({
  props: {
    dataStore: { type: "data_store" },
  },
  async run({ steps, $ }) {
    // Update the value associated with the key, myKey
    await this.dataStore.set("myKey", "newValue");
 
    // Remove the value but retain the key
    await this.dataStore.set("myKey", "");
  },
});

Deleting specific records

To delete individual records in a Data Store, use the delete method for a specific key:

export default defineComponent({
  props: {
    dataStore: { type: "data_store" },
  },
  async run({ steps, $ }) {
    // Delete the lastRanAt record
    const lastRanAt = await this.dataStore.delete("lastRanAt");
  },
});

Deleting all records from a specific Data Store

If you need to delete all records in a given Data Store, you can use the clear method. Note that this is an irreversible change, even when testing code in the workflow builder.

export default defineComponent({
  props: {
    dataStore: { type: "data_store" },
  },
  async run({ steps, $ }) {
    // Delete all records from a specific Data Store
    return await this.dataStore.clear();
  },
});

Viewing store data

You can view the contents of your data stores in your Pipedream dashboard. From here you can also manually edit your data store’s data, rename stores, delete stores or create new stores.

Using multiple data stores in a single code step

It is possible to use multiple data stores in a single code step, just make a unique name per store in the props definition. Let’s define 2 separate customers and orders data sources and leverage them in a single code step:

export default defineComponent({
  props: {
    customers: { type: "data_store" },
    orders: { type: "data_store" },
  },
  async run({ steps, $ }) {
    // Retrieve the customer from our customer store
    const customer = await this.customer.get(steps.trigger.event.customer_id);
    // Retrieve the order from our order data store
    const order = await this.orders.get(steps.trigger.event.order_id);
  },
});

Workflow counter example

You can use a data store as a counter. For example, this code counts the number of times the workflow runs:

export default defineComponent({
  props: {
    dataStore: { type: "data_store" },
  },
  async run({ steps, $ }) {
    // By default, all database entries are undefined.
    // It's wise to set a default value so our code as an initial value to work with
    const counter = (await this.dataStore.get("counter")) ?? 0;
 
    // On the first run "counter" will be 0 and we'll increment it to 1
    // The next run will increment the counter to 2, and so forth
    await this.dataStore.set("counter", counter + 1);
  },
});

Dedupe data example

Data Stores are also useful for storing data from prior runs to prevent acting on duplicate data, or data that’s been seen before. For example, this workflow’s trigger contains an email address from a potential new customer. But we want to track all emails collected so we don’t send a welcome email twice:

export default defineComponent({
  props: {
    dataStore: { type: "data_store" },
  },
  async run({ steps, $ }) {
    const email = steps.trigger.event.body.new_customer_email;
    // Retrieve the past recorded emails from other runs
    const emails = (await this.dataStore.get("emails")) ?? [];
 
    // If the current email being passed from our webhook is already in our list, exit early
    if (emails.includes(email)) {
      return $.flow.exit("Already welcomed this user");
    }
 
    // Add the current email to the list of past emails so we can detect it in the future runs
    await this.dataStore.set("emails", [...emails, email]);
  },
});

TTL use case: temporary caching and rate limiting

TTL functionality is particularly useful for implementing temporary caching and rate limiting. Here’s an example of a simple rate limiter that prevents a user from making more than 5 requests per hour:

export default defineComponent({
  props: {
    dataStore: { type: "data_store" },
  },
  async run({ steps, $ }) {
    const userId = steps.trigger.event.userId;
    const rateKey = `ratelimit:${userId}`;
 
    // Try to get current rate limit counter
    let requests = await this.dataStore.get(rateKey);
 
    if (requests === undefined) {
      // First request from this user in the time window
      await this.dataStore.set(rateKey, 1, { ttl: 3600 }); // Expire after 1 hour
      return { allowed: true, remaining: 4 };
    }
 
    if (requests >= 5) {
      // Rate limit exceeded
      return { allowed: false, error: "Rate limit exceeded", retryAfter: "1 hour" };
    }
 
    // Increment the counter
    await this.dataStore.set(rateKey, requests + 1);
    return { allowed: true, remaining: 4 - requests };
  },
});

This pattern can be extended for various temporary caching scenarios like:

Session tokens with automatic expiration
Short-lived feature flags
Temporary access grants
Time-based promotional codes

Supported data types

Data stores can hold any JSON-serializable data within the storage limits. This includes data types including:

Strings
Objects
Arrays
Dates
Integers
Floats

But you cannot serialize Functions, Classes, or other more complex objects.

Getting Started

Connect

Workflows

Platform

Additional Resources

Using the data store

Saving data

Setting expiration (TTL) for records

Updating TTL for existing records

Retrieving keys

Checking for the existence of specific keys

Retrieving data

Retrieving all records

Deleting or updating values within a record

Deleting specific records

Deleting all records from a specific Data Store

Viewing store data

Using multiple data stores in a single code step

Workflow counter example

Dedupe data example

TTL use case: temporary caching and rate limiting

Supported data types

​Using the data store

​Saving data

​Setting expiration (TTL) for records

​Updating TTL for existing records

​Retrieving keys

​Checking for the existence of specific keys

​Retrieving data

​Retrieving all records

​Deleting or updating values within a record

​Deleting specific records

​Deleting all records from a specific Data Store

​Viewing store data

​Using multiple data stores in a single code step

​Workflow counter example

​Dedupe data example

​TTL use case: temporary caching and rate limiting

​Supported data types

Using the data store

Saving data

Setting expiration (TTL) for records

Updating TTL for existing records

Retrieving keys

Checking for the existence of specific keys

Retrieving data

Retrieving all records

Deleting or updating values within a record

Deleting specific records

Deleting all records from a specific Data Store

Viewing store data

Using multiple data stores in a single code step

Workflow counter example

Dedupe data example

TTL use case: temporary caching and rate limiting

Supported data types