Beeceptor
Webhook.site
Hoppscotch
MockServer
Mockoon
Request inspector
API Fortress
CurlHub.io
Google BigQuery
Databricks
Looker
Jupyter
Presto DB
Amazon EMR
Google Cloud Dataflow
Rakam
If you've ever found yourself stuck during software development because a micro-service or 3rd party API wasn't available, then API Mocking is the solution you've been looking for. Beeceptor is a versatile tool that can help you with many different API development use cases. Whether you need to create mock Rest APIs in seconds, inspect payloads of any HTTP request, or simulate latencies and timeouts, Beeceptor has got you covered. Here are just a few of the ways that Beeceptor can help you:
Mocking: With Beeceptor, you can easily build mock Rest APIs without any coding required. You can also customize responses to simulate various scenarios, such as API failures or edge cases.
UI development: Don't let backend APIs that are still in development block the UI development. Use Beeceptor to mock the APIs and keep your development process moving forward.
Webhooks & Local Tunnel: This allows you to expose a local server to the internet securely. This can be useful for testing APIs or webhooks that require a publicly accessible endpoint.
Dummy Data Generation: Beeceptor also has a powerful fake data generation engine that allows you to create fake data and make the APIs look realistic.
Service Virtualization: With Beeceptor, you can create virtual services that mimic the behavior of real systems or services. This can be useful for testing and development purposes, as well as for isolating and resolving issues in complex systems.
Beeceptor Google BigQueryBeeceptor's answer
Beeceptor stands out for its simplicity and ease of use, particularly for intercepting and mocking real-time HTTP and HTTPS requests without requiring code changes, extensive setup, new dependencies, etc.
Beeceptor's answer
Beeceptor's primary audience includes software developers, QA engineers, and product managers who are involved in the development and testing phases of web and mobile applications.
Based on our record, Google BigQuery should be more popular than Beeceptor. It has been mentiond 47 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Webhook.site exists. Beeceptor exists. Ngrok exists in this space. - Source: dev.to / 3 months ago
This is exactly where Beeceptorโs stateful mocking come in to transform your development workflow. You can implement real data persistence without requiring to set up a single database, instantly unblocking your frontend and QA teams. - Source: dev.to / 9 months ago
Visit Mockbin.io, Beeceptor or RequestBin and click "Create endpoint." These platforms instantly generate a unique URL that captures incoming HTTP requests. Copy the provided URL, something like https://your-webhook-endpoint.com/hook. - Source: dev.to / 10 months ago
Beeceptor: A no-code solution offering real-time request inspection and customizable responses. It's extremely easy to set up, making it perfect for quick prototyping. - Source: dev.to / over 1 year ago
Got nothing to do with spring. It means setting up something like: https://beeceptor.com/. Source: over 3 years ago
We migrated the analytics layer to Google BigQuery. Same queries that timed out in PostgreSQL now run in under 2 seconds. But not everything belongs in BigQuery โ we initially moved too aggressively and actually reverted some queries back when the added complexity wasn't justified. Our rule of thumb: if a query scans hundreds of thousands of rows or involves complex time-series aggregations, BigQuery. Everything... - Source: dev.to / 3 months ago
Google BigQuery - For large-scale data processing and SQL-based analysis. - Source: dev.to / 4 months ago
Data Pipelines usually read from tables that change over time. Most of these tables are stored in a data warehouse like Amazon Redshift or Google BigQuery. Rows are added or removed. Backfills happen. A column gets renamed or its meaning changes. Even when teams snapshot data, those snapshots are often implicit, not recorded as part of the pipeline run itself. - Source: dev.to / 5 months ago
SQL endures because it's the non-negotiable interface for relational data. Enterprise data storage still relies heavily on relational databases despite new alternatives. What makes SQL valuable for learners is transferabilityโwhile dialects differ across PostgreSQL, SQL Server, and BigQuery, the fundamentals stay consistent. - Source: dev.to / 7 months ago
Within classic cloud data warehouses, Google BigQuery presents a different pricing model. Its on-demand, per-terabyte-scanned pricing can be cost-effective for sporadic forensic queries. But it carries the risk of a runaway query where a single mistake leads to a massive bill. - Source: dev.to / 8 months ago
Webhook.site - Instantly generate a free, unique URL and email address to test, inspect, and automate (with a visual workflow editor and scripts) incoming HTTP requests and emails.
Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.โWhat is Apache Spark?
Hoppscotch - Open source API development ecosystem
Looker - Looker makes it easy for analysts to create and curate custom data experiencesโso everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.
MockServer - Easy mocking of any system you integrate with via HTTP or HTTPS.
Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.
