Testim
Selenium
mabl
Cypress.io
Katalon
RainforestQA
Testsigma
TestRail
Google BigQuery
Databricks
Looker
Jupyter
Presto DB
Amazon EMR
Google Cloud Dataflow
Rakam
Testim gives you the flexibility to create and manage tests your wayโcodeless, coded, or both. - Quickly click through UI scenarios, add validation steps, create reusable groups, or export to code and edit in your IDE. - Run suites or test plans in parallel, across multiple browsers, and report results. - Configure validations, modify conditions, or insert custom code or data to test any scenario. - Connect to your CI, version control, collaboration, bug capture, or 3rd party testing grids. - Development Kit - export your tests to code or write them in your IDE using the Testim JavaScript library, API commands, and example code. - Self-healing - Smart Locators learn with each run to stabilize tests, maintaining test stability even when code changes. - Root Cause Analysis - errors are aggregated giving you quick insight into where tests are failing. View rich data including HTML/DOM and before/after screenshots see how attributes changed
Testim Google BigQueryTestim is recommended for development teams, QA engineers, and product managers who face frequent test maintenance challenges and those who work within Agile and DevOps environments. It is especially beneficial for organizations seeking to automate frontend tests for web applications and needing a tool that scales with the complexity and size of their products.
Based on our record, Google BigQuery seems to be a lot more popular than Testim. While we know about 47 links to Google BigQuery, we've tracked only 4 mentions of Testim. 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.
Automated Testing: Platforms like Testim and Selenium use AI to automate the testing process, reducing the time and effort needed for manual testing. - Source: dev.to / almost 2 years ago
Does anyone have any experience with testim.io? A In my company, they created a focus group/team to research this tool and I am part of the team? If you have 1st hand experience using it, please share your feedback. Source: about 4 years ago
Last month, I started exploring solutions for the above problems and one day landed with testim.io. Testim not only automates the flow but also automates code generation for the test scripts. Letโs take a look together. - Source: dev.to / about 4 years ago
I'm seeing the comments and a lot of great suggestions. Curious if anyone has had any experience using testim.io, and how that compares to the most popular one in this thread test cafe. Source: about 5 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 / 4 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 / 6 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 / 8 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 / 9 months ago
Selenium - Selenium automates browsers. That's it! What you do with that power is entirely up to you. Primarily, it is for automating web applications for testing purposes, but is certainly not limited to just that.
Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.โWhat is Apache Spark?
mabl - Agentic Test Automation Platform
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.
Cypress.io - Slow, difficult and unreliable testing for anything that runs in a browser. Install Cypress in seconds and take the pain out of front-end testing.
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.
