The Total Economic Impact™ Of Airbyte

Increased Data Engineer Productivity

Evidence and data. Forrester research states: “It’s no longer enough to build the best pipeline; data engineers need to excel at effective communication and collaboration with business partners to master the ever-changing business insight landscape.”⁴ Interviewees said that while data engineers are the primary users of Airbyte, they work closely with business analysts to understand and map data outcomes. They explained that engineer effort to build, maintain, and troubleshoot data pipelines decreased due to Airbyte’s connector library, accessible UI, and data reliability.

• The senior software engineer at a real estate organization said: “Now there is a standard way to [set up connectors], which helps to accelerate tasks. In order of magnitude [for setting up connectors before and after Airbyte] … it is days versus hours. It really depends on the maturity of tooling the individual teams were using before.”

• The senior manager of data platform engineering at an entertainment organization shared a few different examples of productivity:

  • Troubleshooting. “Instead of troubleshooting issues with our old solution, the data engineers can spend their time ensuring we have healthy pipelines and data stewardship. Troubleshooting and fixing is probably the biggest return on investment for my team. Being able to quickly diagnose saves tens of hours a month.”
  • Building. “Being able to have both custom connectors and very reliable off-the-shelf connectors allowed us to get a lot faster. Airbyte’s no-code solution has also been very helpful for my team on getting started with very generic APIs and being able to integrate those fast. I estimate it saves tens of hours a month. … Before Airbyte, we were building a handful of pipelines. Now, about 40% of our connectors are [things we developed and custom-built] over two years.”
  • Data requests. “It is probably 10 hours a month overall [in] time savings when fulfilling data requests for the procurement and fulfillment teams.”

• The data engineer at a marketing organization said:

  • Maintenance. “It used to take five-FTE team to manage these pipelines earlier when it was built using homegrown technology. Now one person spends 10% of time to maintain these pipelines. That’s a direct reduction in manpower.”
  • Development. “It took us a month to build, test, and deploy custom code for an ads ingestion pipeline. Getting the same exact output [for the same solution] took two days in Airbyte. That is a 10 times decrease in development.”

• The head of tech and security at a marketing organization said:

  • Development. “Without Airbyte, it takes 30% to 40% more time to build a data pipeline. We have existing code [within Airbyte] that can be used to handle the pain of software development that added time in the old process.”
  • Troubleshooting. “By having the business sit in the call as early as possible and tell what they want to do … it saves back-and-forth time for engineering to get ahead of potential glitches.”

Modeling and assumptions. For the financial analysis as applied to the composite organization, Forrester assumes:

• The composite organization builds 100 new pipelines per year.

• Prior to Airbyte, it took 40 hours to build a pipeline.

• With Airbyte the time to build a pipeline is reduced by 60%.

• Prior to Airbyte, it took 60 hours to manage and maintain a pipeline.

• With Airbyte the time is reduced by 40%.

• Fifty percent of the recaptured time is spent on productive activities.

• The average fully burdened hourly salary for a data engineer is $97.

Risks. This benefit may vary among organizations depending on:

• The number and complexity of pipelines built.

• Existing processes in place to manage and maintain pipelines.

• The average salary for a data engineer.

Results. To account for these risks, Forrester adjusted this benefit downward by 15%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $723,000.

Reduction In Infrastructure Management Labor

Evidence and data. Interviewees shared that in addition to data engineers, platform infrastructure teams also gained productivity. The effort previously required to maintain underlying compute and networking components, as well as team access, decreased after the transition to Airbyte’s managed solution.

• The staff engineer at a marketing organization said: “The infrastructure team has seen a reduction in effort. It’s now much easier to onboard teams and to troubleshoot because there is one platform and one paradigm. It is much easier for us cognitively, whereas before we had all those custom repositories with custom tooling and different tech stacks, some of which were not maintained properly. It is now much easier for us to support the average user.”

• The same interviewee said: “I can only imagine that if we didn’t have Airbyte, our team would not be able to do anything else in the data platform. We would be blocked by maintenance. Right now, the team spends 10% of their time on these tasks with Airbyte.”

• The head of tech and security at a healthcare organization said: “There’s always a big benefit in having a managed system. Management includes the infrastructure behind the scenes. Storage, compute and network [components] are always painful to maintain.”

Modeling and assumptions. For the financial analysis as applied to the composite organization, Forrester assumes:

• The work of one infrastructure engineer is repurposed in transitioning to Airbyte.

• The average annual fully burdened salary for an infrastructure engineer is $175,000.

Risks. This benefit may vary among organizations depending on the number of resources dedicated to data platform infrastructure management in the prior environment.

Results. To account for these risks, Forrester adjusted this benefit downward by 15%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $371,000.

Incremental Profit Growth

Evidence and data. Forrester research states: “CDP solutions create new business opportunities to quickly ingest and process new data sets through automation with low-code and no-code capabilities.”⁵ It also notes that CDPs operate on elastic cloud infrastructure that enables organizations to simulate new patterns and insights.

The interviewees shared examples of how improving data accuracy and availability led to revenue and profit impacts for their organizations.

• The staff engineer at a marketing organization said: “The accuracy has significantly increased for a large portion of our pipelines. Before, we would have at least three different questions about why data is not matching with five different sources, and every day there would be a failure. …Ultimately, our shareholders were burdened with incorrect data, [which was passed] to our marketing teams, who would be incorrectly bidding on traffic, therefore decreasing the bottom line on our profit margins. We drastically improved shareholder value implementing this solution.”

• The head of tech and security at a healthcare organization said: “The organization is able to process more data. We are able to capture revenue faster as it allows the organization to fill customer contracts faster. We have around 150 customers per year, and we are able to get 20% more customers each year.”

• The senior manager of data platform engineering at an engineering organization said, “Because Airbyte helps to move data around our systems, we have better insight into what our customers are interacting with across the organization.”

Modeling and assumptions. For the financial analysis as applied to the composite organization, Forrester assumes:

• The composite generates $2 billion in annual revenue.

• It has a 12% operating margin.

• Airbyte is attributed a 0.05% revenue increase in Year 1, a 0.10% increase in Year 2, and a 0.15% increase in Year 3.

Risks. This benefit may vary among organizations depending on:

• Annual revenue.

• Operating margins.

• The extent to which the organization uses data to drive revenue impacting objectives.

Results. To account for these risks, Forrester adjusted this benefit downward by 20%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $462,000.

Unquantified Benefits

Interviewees mentioned the following additional benefits that their organizations experienced but were not able to quantify:

• Data reliability improvement. Interviewees explained that the consistency at which data is refreshed and available for use by their organizations greatly improved. The senior software engineer at a real estate organization said: “We have teams that are able to run jobs a lot more frequently and have more up-to-date data. Instead of running daily jobs, we have teams running them every 10 minutes.”

The senior manager of data platform engineering at an entertainment organization said: “One of our major data sources is related to our e-commerce sales. Before, that pipeline could take sometimes a day or two [to load] after a massive new sale would happen. The e-commerce team wants to see the results of sales from these transactions so they can start developing their next content drop. By virtue of it sometimes taking 48 hours to get fully in sync, we had to figure out a better solution, and now Airbyte can basically live sync data in almost near real time.”

• Data quality improvement. Interviewees expressed that having access to improved data troubleshooting and maintenance led to an increase in data quality and accuracy. The senior manager of data platform engineering at an entertainment organization said: “Being able to have near real time and live troubleshooting for datasets has allowed us to have a lot of high confidence in the quality of our data.”

• Simplified compliance and regulatory reporting. Interviewees explained that clean, available data eases the burden on tasks such as compliance and regulatory reporting. The senior software engineer at a real estate organization said, “We are able to simplify our internal security compliance reporting by using Airbyte because it is now standardized.” The head of tech and security at a healthcare organization said, “It helps the organization meet regulatory deadlines faster.”

• Increased business user adoption. Interviewees said Airbyte’s user interface is approachable and that nontechnical data teams can understand it to promote self-service. The senior software engineer at a real estate organization said: “It lowers the barrier to entry for certain teams to integrate data in an otherwise complex data environment. The user-facing documentation can help someone [go] from zero to having a table they can query in the destination.”

• Faster, more informed decision-making. Interviewees said using Airbyte led to a systematic shift in the speed with which their organizations could provide insights to business users. The staff engineer at a marketing organization said: “We have drastically reduced the time to insight for the business. Earlier, the lag for some of the sources was T-2 (two days prior) or T-3 (three days prior), and now it is uniformly T-1 (one day prior).”

Flexibility

The value of flexibility is unique to each customer. There are multiple scenarios in which a customer might implement Airbyte and later realize additional uses and business opportunities, including:

• Use case expansion, including AI. Interviewees anticipate continuing Airbyte use across teams and exploring how AI and agentic use cases can drive additional business outcomes. The staff engineer at a marketing organization said: “One consideration that we’re making is to open up to more teams. We have some requests for streaming.”

The senior manager of data platform engineering at an entertainment organization said, “We’re starting to get our toes wet [with] AI, and Airbyte makes sure that any AI capabilities that we’re looking at internally have a lot of high quality, highly reliable data flowing into our data warehouse for use.”

The data engineer at a marketing organization said: “There could be use cases where we can provide marketing information to an agent that can provide information to finance and help them make decisions. These use cases have not been formulated yet.”

Flexibility would also be quantified when evaluated as part of a specific project (described in more detail in Total Economic Impact Approach).

Analysis Of Costs

Quantified cost data as applied to the composite

Airbyte Fees

Evidence and data. Interviewees explained that their organizations pay annual fees for Airbyte Pro based on the number of required data workers. Pricing may vary. Contact Airbyte for additional details.

Modeling and assumptions. For the financial analysis as applied to the composite organization, Forrester assumes:

• The composite uses Airbyte Pro.

• The composite requires five data workers in Year 1, six in Year 2, and seven in Year 3.

Risks. This cost may vary among organizations depending on the number of data workers.

Results. To account for these risks, Forrester adjusted this cost upward by 10%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $386,000.

Implementation, Training, And Ongoing Management Costs

Evidence and data. Many interviewees said their organization implemented Airbyte in an open-source deployment prior to full investment. Implementation time varied depending on the organization’s prior environment, whether homegrown or involving a transition from another data tool. Implementation involved engineering and business teams setting up connectors, configuring user access, and mapping intended data outcomes. On an ongoing basis, the organizations dedicate effort to platform maintenance (e.g., patching, meeting with Airbyte to discuss new solution features).

• The senior software engineer at a real estate organization said: “Our initial upgrade and migration took two months. On an ongoing basis, I spend two weeks out of every three months on ongoing maintenance.”

• The senior manager of data platform engineering at an entertainment organization said: “We first used [Airbyte’s] open-source version, which we were able to have running within two weeks. This included building the first connectors to ensure it works with our integrations. On an ongoing basis, it takes 5% to 10% of the team’s time to keep the platform up and running.”

• The data engineer at a marketing organization said, “Transitioning from our homegrown environment to Airbyte took about eight weeks.”

• The staff engineer at a marketing organization said, “At most, it is 1 to 2 hours per week to maintain the platform.”

• The head of tech and security at a healthcare organization said: “Implementing Airbyte itself took about three months. This included both the business side mapping out the data and the data side setting up the connectors and piping the data.”

• The head of tech and security at a healthcare organization said: “The [Airbyte] team interacts [with us] at least quarterly. Airbyte continues to roll out new software packages and new features.”

Modeling and assumptions. For the financial analysis as applied to the composite organization, Forrester assumes:

• The composite uses Airbyte Pro.

• The composite dedicates 240 hours to initial implementation.

• On an ongoing basis, it dedicates 100 hours to solution administration.

• The average fully burdened hourly salary for a data engineer is $97.

Risks. This cost may vary among organizations depending on:

• The organization’s prior data environment.

• Tools and processes in place.

• The complexity of the data environment.

• Use cases in Airbyte.

Results. To account for these risks, Forrester adjusted this cost upward by 15%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $73,000.