8 Integrations with CodeSquire
View a list of CodeSquire integrations and software that integrates with CodeSquire below. Compare the best CodeSquire integrations as well as features, ratings, user reviews, and pricing of software that integrates with CodeSquire. Here are the current CodeSquire integrations in 2025:
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1
Google Cloud BigQuery
Google
BigQuery is a serverless, multicloud data warehouse that simplifies the process of working with all types of data so you can focus on getting valuable business insights quickly. At the core of Google’s data cloud, BigQuery allows you to simplify data integration, cost effectively and securely scale analytics, share rich data experiences with built-in business intelligence, and train and deploy ML models with a simple SQL interface, helping to make your organization’s operations more data-driven. Gemini in BigQuery offers AI-driven tools for assistance and collaboration, such as code suggestions, visual data preparation, and smart recommendations designed to boost efficiency and reduce costs. BigQuery delivers an integrated platform featuring SQL, a notebook, and a natural language-based canvas interface, catering to data professionals with varying coding expertise. This unified workspace streamlines the entire analytics process.Starting Price: Free ($300 in free credits) -
2
Google Chrome
Google
Connect to the world on the browser built by Google. Google builds powerful tools that help you connect, play, work and get things done. And all of it works on Chrome. With Google apps like Gmail, Google Pay, and Google Assistant, Chrome can help you stay productive and get more out of your browser.Starting Price: Free -
3
GitHub Copilot
GitHub
GitHub Copilot is an AI-powered coding companion that helps developers write, debug, and refactor code faster than ever. Built directly into popular IDEs like VS Code, JetBrains, and Visual Studio, Copilot suggests context-aware code completions and automates repetitive tasks. With Agent Mode, Copilot can plan, write, test, and even submit pull requests—acting like an onboarded team member that understands your repositories. Developers can toggle between advanced models such as GPT-5, Claude Opus 4.1, and Gemini 2.5 Pro to balance speed and depth. Its Copilot Chat and Spaces features bring code, documentation, and project notes together for richer, team-tailored insights. Whether you’re building solo or leading an enterprise project, Copilot enhances productivity and creativity across the entire software lifecycle. The GitHub Copilot coding agent streamlines development by automating repetitive and time-consuming tasks, allowing developers to focus on more complex coding.Starting Price: $10 per month -
4
Jupyter Notebook
Project Jupyter
The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more. -
5
Google Colab
Google
Google Colab is a free, hosted Jupyter Notebook service that provides cloud-based environments for machine learning, data science, and educational purposes. It offers no-setup, easy access to computational resources such as GPUs and TPUs, making it ideal for users working with data-intensive projects. Colab allows users to run Python code in an interactive, notebook-style environment, share and collaborate on projects, and access extensive pre-built resources for efficient experimentation and learning. Colab also now offers a Data Science Agent automating analysis, from understanding the data to delivering insights in a working Colab notebook (Sequences shortened. Results for illustrative purposes. Data Science Agent may make mistakes.) -
6
JupyterLab
Jupyter
Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. JupyterLab is a web-based interactive development environment for Jupyter notebooks, code, and data. JupyterLab is flexible, configure and arrange the user interface to support a wide range of workflows in data science, scientific computing, and machine learning. JupyterLab is extensible and modular, write plugins that add new components and integrate with existing ones. The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include, data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more. Jupyter supports over 40 programming languages, including Python, R, Julia, and Scala. -
7
SQL
SQL
SQL is a domain-specific programming language used for accessing, managing, and manipulating relational databases and relational database management systems.Starting Price: Free -
8
Databricks Data Intelligence Platform
Databricks
The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. The winners in every industry will be data and AI companies. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals. Databricks combines generative AI with the unification benefits of a lakehouse to power a Data Intelligence Engine that understands the unique semantics of your data. This allows the Databricks Platform to automatically optimize performance and manage infrastructure in ways unique to your business. The Data Intelligence Engine understands your organization’s language, so search and discovery of new data is as easy as asking a question like you would to a coworker.
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