Salesforce is a comprehensive platform providing cloud computing services to connect with the best customers and partners. Equipped with a well-structured database of its own, it enables you to easily transfer your data to Amazon S3. This article provides insights into how data can be moved from Salesforce to S3 easily. It also highlights the drawbacks and benefits of different strategies used for the same.
Table of Contents
Note: Currently, Hevo Data doesn’t support S3 as a destination.
What are Salesforce Databases?
Salesforce employs Oracle-powered databases that are robust in functionality and architecture. A variety of integral features make it convenient for all forms of data structuring, organization, and management. It constitutes an architecture with the sole objective of providing a customizable interface for the benefit of the customers.
Why Move Data from Salesforce?
With such an efficient database system in place, why move data from Salesforce in the first place? Well, the cost of storage can be one of the major highlights. With several clients and large chunks of accumulated data, brands can benefit significantly by looking for a cheaper way to store it.
Thus, despite a reliance on the primary database, businesses tend to transfer data from Salesforce to S3. This solves inevitable hassles like sending large files to clients. With data stored in S3, the secure download URL can be sent instead, where clients can download attachments directly. These links will also expire as set by the account holder, so the data’s security can be better maintained.
The data can be better maintained with unlimited storage. This helps to optimize the performance of the primary database. There is no file size limit. All native Salesforce functions such as reports, dashboards, workflows, etc. can be used for efficient management in S3.
These benefits have made it increasingly popular for businesses to move data from Salesforce to S3.
The Integration with AWS and Salesforce
What is Amazon S3?
Amazon S3 enables the functioning of its object storage service with enhanced performance at less cost. It stands for Amazon Simple Storage Service, which is designed to make data management and computing easier for developers.
The interface can store data from millions of applications and companies around the world. This makes size no barrier for any amount of files or big data analytics. It provides a range of cost-effective storage classes which support various data access levels. S3 Storage Class Analysis can be used for low-cost data storage. S3 Lifecycle policy enables to execute efficient data transfers. Even changing access patterns can be handled with S3 Intelligent Tiering.
Thus, businesses prefer efficient storage options like Amazon S3. A range of web services can be employed to store and retrieve any amount of data from any specified location on the internet. It ensures data security, scalability and reliability inexpensively.
Hevo Data, an Automated No-code Data Pipeline, helps you directly transfer data from 150+ sources (including 40+ free sources) like Salesforce to a data warehouse or a destination of your choice in a completely hassle-free & automated manner. What’s more, the in-built transformation capabilities and the intuitive UI means even non-engineers can set up pipelines and achieve analytics-ready data in minutes.
Hevo’s consistent & reliable solution to manage data in real-time allows you to focus more on Data Analysis, instead of Data Consolidation. Take our 14-day free trial to experience a better way to manage data pipelines.Get started for Free with Hevo!
Connecting Salesforce to S3 Using Amazon AppFlow
This method involves using Amazon AppFlow to move data from Salesforce to S3. The basic pre-requisite for this method is having a Salesforce developer account from where the transfer will be made. To run through this process, you need to create an empty S3 bucket for the transfer.
Two steps need to be followed to attain a successful transfer. Start by logging into your account. First, the data need to be made ready for export from your Salesforce account, and it consequently needs to be loaded from Salesforce to S3.
Step 1: Making data export-ready from Salesforce
- To initiate the process, you need to log in to your Salesforce developer account. Go to the Accounts tab and select “All Accounts.” This will give you a view of all the records in the database.
- Here you can specify any details and check all parameters based on which you would want to make the transfer. You can check all data pointers to make sure all the transferable data is in order. This will form the source from where the transfer will take place.
Step 2: Configuring data from Salesforce to S3
- Once ready for export, this data now needs to be loaded from the Salesforce to S3 bucket. The currently empty bucket needs to be linked with a flow. The S3 bucket is required to be in the same AWS region as the flow. To load this data, you need to click on “Create Flow” and fill in the flow details. Next, you need to select the source, which will be Salesforce, in this case.
- Click on “Connect” to enable the connection. Provide the connection name and “Continue.” This will, in turn, open the Salesforce dialog box, which you can view to “Allow Access” to your database.
- Select “Account” from the objects list and then specify the destination details. The destination will be “Amazon S3”, in this case. Choose your specific bucket and specify your flow trigger.
- You can either choose for the flow to run on-demand or schedule it. Select the option to map fields manually further choose “map all fields directly.” Select your data validation preferences and add any filters necessary.
- Once the flow has been created, you can run it until it runs successfully. You can access the extracted records. The link leads to the transferred files, which will hold the extracted information.
These steps enable you to manually load data from Salesforce to S3 using Amazon AppFlow.
Limitations of Manually Transfering Data using AppFlow
Although the process of loading data manually can seem straightforward, several limitations are posed through this method.
- The use of the AWS channel is limited to specific regions. These include – Asia Pacific (Tokyo), Europe (Ireland), US East (N. Virginia), US East (Ohio), and US West (Oregon). For regions other than this, you might not be able to carry out the exports. The S3 bucket being used should also correspond to the same AWS region snapshot for successful export.
- All engine versions don’t support this process. Your system needs to feature MariaDB, PostgreSQL, or MySQL for this export to function. For any other databases, you are likely to face export errors.
- Besides this, this method does not support streaming data. The use of this channel poses a limitation on the number of crawlers and jobs that can be used. The excessive manual attention needed under this method is the most significant shortcoming, which makes it redundant.
This article teaches you how to connect Salesforce to S3 using Amazon Appflow. It first provides a brief overview of what these two services are before diving into the procedure of setting up Salesforce to S3 connection. Finally, the article comes to an end by stating the limitations involved in the method.
What if you want to move your data from Salesforce to any other data warehouse? Don’t worry; Hevo Data comes to your rescue.
Hevo Data provides an Automated No-code Data Pipeline that empowers you to overcome the above-mentioned limitations. Hevo caters to 150+ data sources (including 40+ free sources) and can seamlessly transfer your Salesforce data to to a data warehouse or a destination of your choice in real-time. Hevo’s Data Pipeline enriches your data and manages the transfer process in a fully automated and secure manner without having to write any code. It will make your life easier and make data migration hassle-free.Visit our Website to Explore Hevo
Want to take Hevo for a spin? Sign Up for a 14-day free trial and experience the feature-rich Hevo suite firsthand.