Cost reduction is one of the primary objectives of any business. Modern day data analytics decision makers are no different. They strive to get their hands on a tool or a platform that would enable them to not only perform better data analytics but also help them reduce the cost of the complete data infrastructure. For example, the total cost of ownership of a data infrastructure includes the cloud cost, ETL tool cost and Analytics tools cost.
Its not a hidden secret that moving data from local data centres to cloud based data lakes is much more cost efficient. Generally, cloud providers charge pennies for storing multiple gigabytes of data. For example, Amazon Web Services (AWS) charges a little more than 2 cents per GB of data stored and the incremental cost gets even lower with the rising volume of data.
Once a decision maker is convinced about a storage solution and it serves their use case, the next question that comes to his head is, “ How much will they charge for transferring data?”
Data storage providers generally don’t charge anything or charge very less for uploading data into the cloud. They don’t want to put any restrictions on the data volume uploaded on the cloud. But, when the data is moving out of the cloud, the costs pile up for an organisation. This is referred to as data egress cost.
What is Data Egress ?
Data egress cost is incurred by an organisation when they plan to move out the data from the cloud storage or in other words while exporting the data. Now, there could be multiple reasons for doing this. Some of them include, transfer of data to some other storage, disaster recovery and data movement from an application to a preferred data lake or data warehouse, among others.
The opposite of data egress is data ingress or import of data into the data storage. Generally, there are no charges involved in this process.
Data Egress Cost Analysis : AWS vs GCP vs Azure
While making a decision of choosing the preferred data storage platform, the answer to the question of how much is the data egress cost ? is answered simply by “not much” as compared to the cost of storing the data. For example, the data egress cost at AWS is only 5 to 7 cents higher than the cost of storing the data on a per GB basis. But, this becomes huge, when the data volume grows. And with any growing business, the volume of data is bound to increase resulting in a huge cost for the organization.
Let’s take a quick look at the data egress cost of the leading cloud data storage providers, that is, Amazon Web Services, Google Cloud Platform and Microsoft Azure.
Amazon Web Services
$0.09 per GB up to 10 TB/mo, $0.085 per GB for the next 40 TB
Google Cloud Platform
$0.12 per GB for the first TB, $0.11 per GB up to 10 TB, $0.08 per GB after 10 TB
$0.087 per GB for up to 10 TB, $0.083 per GB for up to 40 TB
Note: All prices are referred from the respective websites
How Sprinkle saves on Data Egress Cost ?
Sprinkle is a data platform built for cloud data warehouses and it doesn’t require any transfer of data outside your cloud infrastructure.
Using Kubernetes, Sprinkle processes and transfers data in the same network. This is much more secured - More secured as data does not move out of network
As seen in the above image, Sprinkle sits within the customer network and no data moves outside the customer network. Hence, there is no data egress cost while using the Sprinkle as compared to some other tools, who move the data outside the customer network.
Q: What are data egress costs?
A: Data egress costs are the charges incurred by businesses when they transfer data out of a cloud provider's network or storage system.
Q: Why is it important to analyze data egress costs?
A: It is important to analyze data egress costs to understand how much it costs to transfer data from a cloud provider's network or storage system and optimize data transfer to reduce costs.
Q: How can businesses analyze their data egress costs?
A: Businesses can analyze their data egress costs by monitoring their data transfer patterns, identifying high-volume and high-cost data transfers, and optimizing their data transfer processes to reduce costs.
Q: What are some best practices for reducing data egress costs?
A: Some best practices for reducing data egress costs include compressing data before the transfer, using caching to reduce frequent data transfers, and using regional data storage to minimize the distance data needs to travel.
Q: How can businesses determine which cloud provider offers the most cost-effective data egress options?
A: Businesses can determine which cloud provider offers the most cost-effective data egress options by comparing the pricing and features of different cloud providers and by conducting tests to evaluate the performance and cost of data transfers.
Q: How can businesses effectively manage their data egress costs?
A: Businesses can ensure they effectively manage their data egress costs by regularly monitoring their data transfer patterns and costs, optimizing their data transfer processes, and working with experts in the field to identify and implement best practices.