Data ingestion costs refer to the expenses associated with loading data into a data warehouse, data lake or other storage systems for processing and analysis. It is incurred when the data is updated, inserted and deleted in the data store.
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Key factors impacting ingestion costs
Ingestion costs largely come down to the throughput and complexity of the data movement.
- Data volume: The more data you move, the higher the cost.
- Frequency of data transfer: Frequent, real-time data syncs are more expensive than periodic batch updates.
- Data complexity: More complex models that require cleaning or transformation increase costs due to higher compute demands.
- Data transfer fees: Cloud providers (e.g. AWS, Azure, Google Cloud) often charge for data movement between regions or services.
- Data ingestion efficiency: Fivetran reduces data ingestion costs through data optimization techniques such as partitioning.
All of these factors directly impact the consumption of compute power during ingestion, i.e. the cost of processing and organizing data.
Fivetran’s role in reducing ingestion costs
Ingestion can consume 20-30% of compute costs in a data warehouse:
"Ingestion costs were a major concern for us, taking up 50% of our warehouse compute. After some optimization, we brought it down to 20% but it remained a significant expense. Transitioning to a data lake architecture with Fivetran has the potential to eliminate these costs entirely, offering even greater savings."
– Leading global manufacturing organization
Fivetran is optimized to load data efficiently. We partner closely with leading cloud providers to ensure the lowest possible ingestion costs for our customers.
The Managed Data Lake Service absorbs ingestion costs
With Fivetran’s Managed Data Lake Service, we take it a step further by covering the costs of ingestion into the data lake, making it even more cost-effective for your business.
The Fivetran Managed Data Lake Service simplifies data lake management by automatically converting customer data to popular open formats (i.e. Apache Iceberg or Delta Lake) before landing it in the data lake. When combined with Fivetran's ongoing table management and maintenance, customers get the easy queryability and ease of use of a cloud data warehouse, with the flexibility and scale of a data lake.
Our service maintains full control over the data ingestion process through a specialized engine optimized for efficiency. The Fivetran Managed Data Lake Service is so effective that we cover the ingestion costs as part of our existing pricing model, incurring these expenses on behalf of our customers.
Who benefits the most?
Organizations with an architecture containing one or more data warehouses stand to gain the most from moving to a data lake architecture.
Data lakes explicitly separate the storage layer of the data warehouse into a separate, vendor-neutral format in object storage. Multiple, specialized execution engines can interact with the same data lake, mediated by a catalog that provides transactions and fine-grained permissions.
With Fivetran’s Managed Data Lake Service, you can::
- Eliminate ingestion costs, as Fivetran absorbs them for data lakes.
- Reduce the need to expensively load data directly into data warehouses.
For large organizations, eliminating 20-30% of total data warehouse costs can result in substantial savings, potentially in the millions. At Fivetran, we have multiple customers who spend over $1 million per year on ingestion costs alone, so this change can lead to substantial savings.
By leveraging a managed data lake, your organization can enjoy the scalability, flexibility and cost-efficiency that come with this architecture. Many of our customers have already made the switch and are reaping the financial benefits.
Interested in reducing your data ingestion costs? Sign up for a free 14-day trial or contact us at [email protected] to learn more.
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