TL;DR Short answer: the best Weatherstack ETL tools are the ones that spend your API calls carefully, because every sync uses calls for every location you track and the free plan allows only 100 a month. Airbyte has a Weatherstack connector for loading current, historical and forecast data into a warehouse, and automation tools such as n8n and Make suit smaller jobs. Historical data needs the Standard plan and forecasts need Professional, whichever tool you choose. Eight Weatherstack ETL tools compared:
Airbyte dlt n8n Make Zapier Pipedream Google Sheets with Apps Script Custom code with Python The Weatherstack constraint: API calls are counted per location per request, so the number of locations multiplied by sync frequency decides which plan you need. Weatherstack ETL tools pull weather data from the Weatherstack API into a warehouse, database or spreadsheet, where it can be joined with sales, demand, logistics or field operations data. Weatherstack, an APILayer product, returns current conditions, historical weather, forecasts and location lookups as JSON for any location you query. For other approaches to adding external data to your records, see our guide to data enrichment tools .
Every Weatherstack ETL tool reads the same REST API, authenticated with an access key and queried by city, postcode, coordinates or IP address. The available data depends on your plan:
Current weather: temperature, feels-like, precipitation, humidity, wind, pressure, visibility, cloud cover and UV index, available on every plan. Historical weather: past conditions for a given date or date range, including hourly data, available from the Standard plan. Forecast: up to 7 days on the Professional plan and 14 days on Business. Location lookup: autocomplete for matching place names to locations, available from the Standard plan. Astronomy and marine data: sunrise, sunset and moon phase on paid plans, and marine conditions on higher tiers. How much does the Weatherstack API cost for ETL? Plan choice matters more for ETL than for an app, because a pipeline makes calls on a schedule for every location. Weatherstack's published plans, as of October 2026:
Plan Price Calls per month What it adds Free $0 100 Current weather only Standard $9.99 a month 50,000 Historical data and location lookup Professional $49.99 a month 300,000 7-day forecast and bulk queries Business $99.99 a month 1,000,000 14-day forecast
A single location synced every hour uses about 720 calls a month, which already exceeds the free plan, and 50 stores refreshed hourly need roughly 36,000. Annual billing reduces the price, and overages are charged per call above your plan's limit.
How do the Weatherstack ETL tools compare? Tool Approach Destinations Best for Cost Airbyte Pre-built Weatherstack connector Any warehouse, lake or database Weather next to sales and operations data Free self-hosted Core; paid Cloud plans dlt Python REST API source DuckDB, BigQuery, Snowflake, Postgres and more Python teams loading a warehouse Free, open source n8n HTTP Request node Databases, sheets, apps Self-hosted automation Free self-hosted; paid cloud Make HTTP module in scenarios Sheets, databases, apps No-code scheduled lookups Operations-based, free tier Zapier Webhooks or code steps Sheets and apps Simple, low-volume lookups Task-based, free tier Pipedream Scheduled code workflows Databases and apps Developers wanting managed scheduling Credit-based, free tier Apps Script Script with a time trigger Google Sheets A few locations in a sheet Free with Google Workspace Custom code Direct API calls Anywhere Exact control Free, engineering time
Which Weatherstack ETL tools should you consider? Eight Weatherstack ETL tools, from a pre-built connector to code:
1. Airbyte Airbyte is the open-source data connectivity platform for AI and analytics, and among Weatherstack ETL tools it is the one with a pre-built connector. Its Weatherstack source has four streams, current, historical, forecast and autocomplete, with full refresh and incremental append syncs, configured with your access key, a location and a historical date. Stream availability follows your Weatherstack plan: current works on every plan, historical and autocomplete need Standard, and forecast needs Professional. For more ELT options, see our guide to ELT tools .
The reason to use Airbyte rather than a script is what sits next to the weather data: sales, orders, delivery and marketing data from 700+ other connectors in the same warehouse, so demand models and operations dashboards can join on date and location. Airbyte runs in Airbyte Cloud, in your own environment with Airbyte Flex, or self-hosted with Airbyte Core.
Pros Cons Pre-built connector with four streams One location per source configuration Weather lands next to business data Stream availability depends on your Weatherstack plan Cloud, Flex or self-hosted Core Each sync spends API calls, so plan frequency carefully
2. dlt dlt is an open-source Python library for loading data. Its REST API source can be pointed at Weatherstack's endpoints with your access key and a list of locations, and dlt infers the schema from the JSON and loads it into DuckDB, BigQuery, Snowflake or Postgres. It suits Python teams that want a warehouse pipeline in code. For more code-first options, see our guide to Python ETL tools .
Pros Cons Schema inference from JSON responses You write and schedule the pipeline Easy to loop over many locations Requires Python skills Free and open source No hosted UI
3. n8n n8n is one of the self-hostable Weatherstack ETL tools: it calls the Weatherstack API with its HTTP Request node on a schedule, then filters, transforms and writes results to a database, spreadsheet or app. It can be self-hosted, which keeps automation costs flat as the number of runs grows.
Pros Cons Self-hosting option You run and maintain it if self-hosted Visual workflows with code nodes Not built for large historical backfills Hundreds of destination integrations Rate and call limits are yours to manage
4. Make Make is the no-code option among Weatherstack ETL tools: it calls the API through its HTTP module inside a scheduled scenario, parses the JSON and routes values to Google Sheets, Airtable, a database or chat tools. It suits teams that want weather data in an operational tool rather than a warehouse.
Pros Cons No-code and quick to set up Operations-based pricing adds up with frequent runs Easy routing to many apps Not designed for warehouse loading Free tier to start Complex scenarios become hard to maintain
5. Zapier Zapier can call Weatherstack with Webhooks by Zapier or a code step on a schedule and pass the results to a spreadsheet, CRM or messaging app. It suits simple, low-volume lookups such as a daily forecast for a few sites.
Pros Cons Very fast to set up Task-based pricing grows with locations and frequency Thousands of destination apps Webhooks are a paid feature Good for alerts and notifications Not suited to historical backfills
6. Pipedream Pipedream runs scheduled workflows where you call the Weatherstack API in a Python or Node.js step and send the results to a database or app, without managing servers. It sits between no-code tools and a self-built service.
Pros Cons Code steps with managed scheduling Credit-based pricing at volume Many prebuilt destination actions Still your logic to maintain Free tier for testing Not built for warehouse-scale history
7. Google Sheets with Apps Script A short Apps Script function can call the Weatherstack API with UrlFetchApp and write temperature and conditions into a sheet, and a time-driven trigger runs it hourly or daily. It is the simplest route for a handful of locations. For more spreadsheet pipelines, see our guide to Google Sheets ETL tools .
Pros Cons Free with Google Workspace Not suited to many locations or long history Easy to share results Apps Script quotas limit run time No extra tools needed Errors are easy to miss without alerting
8. Custom code with Python Calling the REST API directly with Python's requests library gives you full control over which locations you query, how often, and where results go, including combining several locations into bulk queries on plans that support them. You own scheduling, retries and storage. For other API pipelines, see our guide to REST API ETL tools .
Pros Cons Exact control over calls and spend You own scheduling, state and retries No licence cost Ongoing maintenance Any destination Schema changes are yours to handle
Do you need an API for weather data at all? Not always. If you need historical observations rather than live conditions or forecasts, BigQuery's public datasets include NOAA's Global Surface Summary of the Day, which you can query directly without an API or pipeline, and the Snowflake Marketplace offers weather and climate datasets that providers share straight into your account. These suit analysis of past weather against sales or demand. An API such as Weatherstack is the better fit when you need current conditions, forecasts or specific locations on demand. For more on the warehouse side, see our guide to cloud data warehouses .
What should you check before syncing Weatherstack data? Whichever Weatherstack ETL tools you choose, check these first:
Call budget: multiply locations by syncs per month and compare it with your plan, leaving headroom for retries.Plan features: historical data needs Standard and forecasts need Professional, so confirm your plan before building.Location identifiers: use coordinates or stable identifiers rather than free-text city names, which can resolve to the wrong place.Units and time zones: set units explicitly and store the local time and UTC offset that the API returns, so joins with business data line up.History: the API only returns history you request, so backfill the date range you need and store it, rather than re-requesting it.Key security: keep the access key in a secrets manager, since it is passed as a query parameter.How do you start pulling Weatherstack data with Airbyte? If you decide to test Airbyte, setting up a Weatherstack pipeline takes three steps.
Step 1: Set up Weatherstack as a source Sign up at Weatherstack and copy your access key from the dashboard. In Airbyte, open Sources, choose New source, select Weatherstack and enter the access key, the location you want, and a historical date if your plan includes historical data.
Step 2: Set up a destination Pick where your weather data should land, such as BigQuery, Snowflake, Postgres or another database, ideally next to the business data you want to join it with.
Step 3: Configure the connection Select the streams your plan supports and set a sync frequency your call budget can afford. The process is the same whether you start with Airbyte Cloud or run self-hosted Airbyte Core .
Which Weatherstack ETL tool should you choose? Choosing between Weatherstack ETL tools comes down to where the data needs to go. If weather should sit next to sales, orders or operations data in a warehouse, use Airbyte or dlt. If you want results in an app or spreadsheet, n8n, Make, Zapier or Pipedream are faster to set up, and Apps Script is enough for a few locations in a sheet. Whichever you pick, size your plan from locations multiplied by sync frequency first. For another external API source handled the same way, see our guide to News API ETL tools .
Join weather data with your business data Load Weatherstack current, historical and forecast data into the same warehouse as your sales and operations data with Airbyte, in Airbyte Cloud, in your own environment with Airbyte Flex, or self-hosted with Airbyte Core.
Try Airbyte Cloud free for 14 days or talk to our team .
Frequently Asked Questions (FAQs) 1. What are the best Weatherstack ETL tools? Airbyte has a pre-built Weatherstack connector for loading data into a warehouse, and dlt or custom Python code suit code-first teams. For smaller jobs, n8n, Make, Zapier, Pipedream and Google Sheets with Apps Script can call the API on a schedule.
2. Can I get historical weather data from Weatherstack for free? No. The free plan covers current weather only, with 100 calls a month. Historical data starts on the Standard plan, and forecasts need Professional or Business.
3. How many API calls does a Weatherstack pipeline use? Roughly one call per location per sync. One location synced hourly uses about 720 calls a month, so even small pipelines usually need a paid plan.
4. Does Airbyte support Weatherstack? Yes. Airbyte's Weatherstack source syncs current, historical, forecast and autocomplete streams, with stream availability depending on your Weatherstack plan.
5. Are there alternatives to an API for historical weather data? Yes. BigQuery's public NOAA datasets and weather datasets on the Snowflake Marketplace can be queried directly in your warehouse without an API, which suits historical analysis.
Suggested reads Data Enrichment Tools
REST API ETL Tools
Data Ingestion Tools
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