Before you begin using the Similarweb API, ensure that you have:
Similarweb API Key: You need a valid API key to authenticate your requests. If you don't have one yet, follow the instructions in the Authentication section to obtain yours.
To make your first API request, follow these steps:
- Authentication: Acquire your API key by following the instructions in the Authentication section.
- Construct the Endpoint: All API requests start with a base URL followed by the specific endpoint you want to access. Refer to the relevant API endpoint in the API Reference for the correct URL structure.
- Send a Request: Use your preferred programming language or tool to send an HTTP GET or POST request to the constructed endpoint. Don't forget to include your API key in the request headers.
- Receive the Response: The API will respond with data in JSON format. You can parse this data to extract the insights you need for your analysis.
When integrating with the Similarweb API, you have two primary options: REST API and Batch API. Each approach has distinct characteristics and benefits tailored to different use cases.
The Similarweb REST API provides real-time access to web analytics and market intelligence data. It allows you to make individual HTTP requests to specific endpoints, each representing a distinct resource or data set. This approach is ideal for scenarios where you need immediate access to up-to-the-minute data and want to retrieve specific data points on-demand.
- Real-Time Data: Access data in real-time, ensuring you have the latest insights at your fingertips.
- Granular Control: Make precise requests for specific data, optimizing bandwidth and minimizing data transfer.
- Immediate Integration: Quickly integrate data into your applications or systems, enabling dynamic, up-to-date features.
The Similarweb Batch API, on the other hand, is designed for handling large-scale data extraction tasks. Instead of making individual requests for each piece of data, you submit batch jobs that specify the data you need and receive the results when the job is complete. This approach is suitable for scenarios where you require extensive historical data, long-term trend analysis, or periodic data updates.
- Efficient Data Retrieval: Retrieve large datasets of up to one million domains in a single request, reducing the overhead of multiple API calls. Reports can be sent directly to your own database systems including S3 and Snowflake.
- Scheduled Updates: Schedule batch jobs to run at specific times or intervals, fully automating data retrieval tasks.
- Historical Analysis: Access historical data of up to five years for in-depth trend analysis and long-term insights.
- Optimized for Large-Scale Needs: Ideal for applications that require extensive data sets, such as market research or historical trend analysis.
Updated 3 months ago