Nowadays, data has become one of the most priceless assets for any business model. Companies are using data in various aspects but as their business grows, the idea of storing all that data in a secure and centralized location becomes a huge question to them. This is where a Cloud-based Data Warehouse comes into the picture. A Cloud-based Data Warehouse loads all your data into a centralized location gives you the privilege of on-demand computing, increased computing capacity, and seemingly limitless storage capacity. One of the leading Cloud-based Data Warehousing solutions is Snowflake.
Snowflake allows you to extract data from multiple locations, transform that data into a specific format and then store it into a centralized location. GitHub Snowflake Integration is one of the most popular integrations out in the market which is majorly used by developers to store their project data and use it comfortably as, when, and where required.
The article introduces you to GitHub and Snowflake, including their key features. It also introduces you to GitHub Snowflake Integration and provides you with 2 different approaches to set up GitHub Snowflake Integration. It also provides the limitations of using Manual integration and at the same the advantages of using Automated Integration.
Table of Contents
- Introduction to GitHub
- Introduction to Snowflake
- Methods to Set Up GitHub Snowflake Integration
- Advantages of Integrating GitHub Snowflake
Introduction to GitHub
GitHub is a Cloud-based Service that helps developers to collaborate and work on their projects. It also helps in storing and managing your code. GitHub also allows you to track the changes in your code and at the same time control these changes. It works on 2 major principles:
- Version Control
Version Control, in simple terms, keeps track of all your changes made to your project and also keeps a record of all these changes. With Version Control, you can access, compare and update different versions of your project. It also allows you to roll back to a previous version in case of any errors or differences. It is very useful while working in a team.
- Tracking History: Keeping track of every change you make to your project. Assume that you make some changes to your CSS file (add some new styles and deleted a few old styles). Everything is going smoothly but a month later you discover that your changes broke the layout on a few pages. Now, instead of trying to remember what code you adjusted a month ago, you can use Git that will provide you with information regarding those changes (date, file name, etc.).
- Collaboration: It is the process of tracking the changes, comparing and merging your code. Git makes collaboration very easy and allows you to be more productive when working in a team. With this, you do not need to just sit around and wait for the other person to make his/her changes before moving forward. You can continue working on your changes without worrying about recurrency in your code.
- Feature Branch: It is simply an independent branch in your Git Repository that focuses on a specific section of your project. You can hop through the branches make changes to them. Once the branch is completely ready, you can merge it with the main branch/code. This allows your team to work on different parts of the project at the same time.
Key Features of GitHub
Listed below are some of the key features of GitHub:
- Project Management: With Version Control in GitHub that keeps track of all the changes made in your project, it becomes easy to manage your project and collaborate with other developers.
- Effective Team Management: With GitHub, all the team members can stay updated with all that is happening on the project. This helps in staying organized and well-coordinated.
- Improve Code Writing: With the GIt commands, you can review, improve and propose new codes for your project. It also makes sure that all your codes are safely loaded into GitHub’s Cloud Storage.
For more information on GitHub, click here.
Introduction to Snowflake
Snowflake is a Cloud-based Data Warehousing Solution and is one of the kind as it works on Hybrid Architecture. The Hybrid Architecture has both Shared-Disk and Shared-Nothing elements which work simultaneously to process all your queries. In Shared-Disk Architecture, although the data processing is performed on multiple nodes, they do not have individual memory. All the nodes are connected by a single memory disk that allows them to access all the data.
In Shared-Nothing architecture, the nodes work independently and do not share the same memory or storage. Furthermore, it processes the data in parallel (using multiple nodes) that increases the performance of the Data Warehouse, and also results in more effective and efficient processing of SQL queries. Because of its architecture, Snowflake is one the fastest Data Warehousing Solution to any business model. Its performance speed is phenomenal and takes only seconds to run your SQL queries.
Key Features of Snowflake
Listed below are some of the key features of Snowflake:
- Data Backup and Recovery: Snowflake supports Time Travel that allows you to query, clone, and restore data for up to 90 days. This is highly beneficial during the time of data loss. It also has the Fail-Safe feature that offers disastrous recovery of historical data within 7 days of losing your data.
- Scalability: Snowflake sets apart computing and storage units that enable both Horizontal and Vertical Scaling. It also allows you to choose between Maximized and Auto-Scale Modes. The Maximized Mode allows you to specify the same value for both maximum and minimum clusters. Snowflake runs all the clusters simultaneously. While in Auto-Scale Mode, you can give specific values for maximum and minimum clusters. Snowflake takes the charge of handling the clusters and dynamically starts and stops the clusters as per the load.
- Security: Snowflake controls site access through network policies, private communication between Snowflake and your VPCs, and your VNets through AWS Privat Link and Azure Private Link respectively. It uses the system for Cross-domain Identity Management (SCIM) to manage user and group administration. It also supports Key Pair Authentication, Key Pair Rotation, Multi-Factor Authentication (MFA), OAuth, and Single sign-on (SSO) for a more secure account or user authentication. Snowflake encrypts all the data by default using AES-256 strong encryption and uses Column-level security for masking column data.
For more information on Snowflake, click here.
Methods to Set Up GitHub Snowflake Integration
This method entails manually setting up GitHub Snowflake Integration. The method is divided into 2 major parts. In the first part, you will have to manually export GitHub data in CSV format using custom scripts and then in the second part, you will have to import that data into your Snowflake Data Warehouse. This method demands technical proficiency and working experience in GitHub and Snowflake platforms.
Hevo provides a hassle-free solution that helps you set up GitHub Snowflake Integration without any intervention in an effortless manner for free. Hevo is fully managed and completely automates the process of not only loading data from your desired source but also enriching the data and transforming it into an analysis-ready form without having to write a single line of code.
Hevo’s pre-built integration with GitHub (Data Source Available for Free in Hevo), among other 100+ data sources, will take full charge of the data transfer process, allowing you to focus on key business activities. Get started with Hevo today!Sign up here for a 14-day Free Trial!
Methods to Set Up GitHub Snowflake Integration
Now that you have a basic understanding of Github and Snowflake, let’s walk through the methods to set up GitHub Snowflake Integration. There are majorly 2 methods to set up GitHub Snowflake Integration:
- Method 1: Setting Up Manual GitHub Snowflake Integration
- Method 2: Setting Up GitHub Snowflake Integration using Hevo
The first method is Manual Integration while the second method uses Hevo, which is one of the best No-code Data Pipeline platforms, to set up GitHub Snowflake Integration.
Let’s walk through these methods one-by-one in detail.
Method 1: Setting Up Manual GitHub Snowflake Integration
Follow the steps below to set up GitHub Snowflake Integration manually:
- Step 1: Export Files from GitHub in CSV Format
- Step 2: Import the Files into Snowflake Data Warehouse
Step 1: Export Files from GitHub in CSV Format
Follow the steps below to export the files from GitHub in CSV format:
- Log in to your GitHub account and go to the project repository.
- Go to the file you want to export. You can also view the content of the file within the GitHub User Interface (UI). Click on the file to view its content.
- Now, right-click the “Raw” button. You will find this button at the top right corner of your screen.
- Once done, click on “Save as”. Click on the location where you want to save this file after giving it a name of your choice.
Step 2: Import the Files into Snowflake Data Warehouse
Now, that you have exported all the files, it’s time to import these files into Snowflake Data Warehouse. Here, you will be using the PUT SQL command to load your CSV data file from your local system to Snowflake Internal Stage and then you will be using the COPY INTO SQL command to load the file from Snowflake Internal Stage to Snowflake Database Table as shown in the image below.
Follow the steps below to import the files into Snowflake Data Warehouse and set up GitHub Snowflake Integration:
- Upload the CSV file from the local system to Snowflake Internal Stage using the PUT SQL command. Use the following SQL query for the same.
NOTE: By default, the PUT command compresses your file using GZIP.
PUT file:///apps/sparkbyexamples/emp.csv @%EMP;
- Now, load the CSV file from Snowflake Internal Stage to Snowflake Table using the COPY INTO SQL command. For this step, first, you will have to create a Snowflake Table. Use the following SQL query to create a new Snowflake Table.
NOTE: Change the column names as per your requirement.
CREATE TABLE EMP (FNAME VARCHAR, LNAME VARCHAR, SALARY VARCHAR, DEPARTMENT varchar, GENDER varchar);
- Now use the COPY INTO SQL command to load the file that you compressed in the last step into Snowflake Table that you created just now. Use the following for the same:
COPY INTO EMP from '@%EMP/emp.csv.gz';
That’s it. You have successfully set up manual GitHub Snowflake Integration.
Limitations of Setting Up Manual GitHub Snowflake Integration
Listed below are the limitations of manually setting up GitHub Snowflake Integration:
- Setting up Manual GitHub Snowflake Integration requires technical expertise and experience in working with both GitHub and Snowflake. It would be very difficult for anyone with no or little technical experience to successfully integrate these 2 platforms.
- As you will need to export and import data periodically, there is a high possibility of Data Redundancy.
- Manual Integration is only effective when you have files in CSV format. If that is not the case, then it would be impossible to set up GitHub Snowflake Integration.
To avoid these limitations, you can set up GitHub Snowflake Integration using Hevo as it is a seamless and hassle-free integration method.
Method 2: Setting Up GitHub Snowflake Integration using Hevo
Hevo Data, a No-code Data Pipeline helps to Load Data from any data source such as Databases, SaaS applications, Cloud Storage, SDKs, and Streaming Services and simplifies the ETL process. It supports 100+ data sources including GitHub, etc., for free and is a 3-step process by just selecting the data source, providing valid credentials, and choosing the destination. Hevo loads the data onto the desired Data Warehouse, enriches the data, and transforms it into an analysis-ready form without writing a single line of code.
Its completely automated pipeline offers data to be delivered in real-time without any loss from source to destination. Its fault-tolerant and scalable architecture ensure that the data is handled in a secure, consistent manner with zero data loss and supports different forms of data. The solutions provided are consistent and work with different Business Intelligence (BI) tools as well.Get Started with Hevo for free
Check out why Hevo is the Best:
- Secure: Hevo has a fault-tolerant architecture that ensures that the data is handled in a secure, consistent manner with zero data loss.
- Schema Management: Hevo takes away the tedious task of schema management & automatically detects the schema of incoming data and maps it to the destination schema.
- Minimal Learning: Hevo, with its simple and interactive UI, is extremely simple for new customers to work on and perform operations.
- Hevo Is Built To Scale: As the number of sources and the volume of your data grows, Hevo scales horizontally, handling millions of records per minute with very little latency.
- Incremental Data Load: Hevo allows the transfer of data that has been modified in real-time. This ensures efficient utilization of bandwidth on both ends.
- Live Support: The Hevo team is available round the clock to extend exceptional support to its customers through chat, email, and support calls.
- Live Monitoring: Hevo allows you to monitor the data flow and check where your data is at a particular point in time.
Advantages of Integrating GitHub Snowflake
Listed below are some of the major advantages of setting up GitHub Snowflake Integration:
- GitHub Snowflake Integration allows you to store all the historical data in a centralized location. This makes it easier for you to fetch this information as and when required. Moreover, it also allows you to run this data through Business Intelligence tools and extract meaningful insights out of it.
- As all your data will be stored in a centralized location, this will allow everyone in your team to use that data without even downloading it. The data could be huge and the elimination of the step where you had to download it for future use, makes it so much easier for you to use the data in your projects.
The article introduced you to GitHub and Snowflake. It also introduced you to GitHub Snowflake Integration and provided you with a comprehensive guide that you can use while setting up GitHub Snowflake Integration. The article included 2 different approaches to set up GitHub Snowflake Integration. The first method is completely manual while the second method uses Hevo Data No-code Data Pipeline for automated integration.
With the complexity involves in Manual Integration, businesses are leaning more towards Automated Integration. This is not only hassle-free but also easy to operate and does not require any technical proficiency. In such a case, Hevo Data is the right choice for you! It will help simplify the ETL Process process by setting up GitHub Snowflake Integration for free.Visit our Website to Explore Hevo
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Share your experience of setting up GitHub Snowflake Integration in the comments section below!