지금 Current 2022: The Next Generation of Kafka Summit에 등록해서 데이터 스트리밍의 미래를 라이브로 확인해 보세요!
If you’re reading this, it’s likely because you are leveraging (or considering) Apache Kafka® in your organization—especially as it has become the de facto standard for data streaming. Adopted by over 70% of the Fortune 500, Kafka has been tapped to anchor modern data architectures and power rich, digital customer experiences and software-driven business operations in real time.
However, fully realizing value on your own with open source Kafka is a multi-year journey requiring significant investment. Building and maintaining a reliable, secure, and scalable Kafka deployment in-house comes with significant costs and burdens—ones that only grow over time. Capacity needs to be planned, clusters sized and rebalanced, failover and scaling processes designed—not to mention the additional tooling required as Kafka usage scales including connectors, high availability, enterprise-grade security, data governance, and more.
Most modern organizations do not want to be in the business of managing data infrastructure, but many struggle to quantify the challenges and risks they face in order to make the case to offload this burden. We commissioned Forrester, a trusted name in market research, to deliver a Total Economic Impact study that quantifies the cost savings and benefits your business can achieve when you offload the burden of self-managing Kafka to Confluent’s cloud-native, complete, and fully managed data streaming service.
“The top consideration for moving to Confluent Cloud was
scalability. And the second was to relieve our engineers from operation and maintenance duties.”
— Manager of data engineering, Internet TV services
Forrester identified TCO savings of nearly $2.58 million for businesses that used Confluent instead of self-supporting open source Kafka in-house. Their research included interviewing multiple customers with experience using Confluent, understanding their costs and challenges with managing open source Kafka on their own, and then aggregating their experiences and benefits to determine the true value that Confluent can help organizations realize.
All told, Forrester determined that using Confluent Cloud delivered an overall 257% return on investment (ROI) with a payback period of less than six months.
Forrester identified key savings across the following categories:
“After switching to Confluent Cloud, the engineering workload on maintenance and operations reduced almost down to nothing, compared to our prior state. We used to have at least two dedicated engineers to monitor, maintain, and upgrade.”
-Head of data engineering and integration, e-commerce firm
Creating a reliable, secure, and scalable Kafka platform in-house is costly and burdensome—especially as your streaming needs grow. Not to mention the risk you bear of business-disrupting downtime with increasingly mission-critical streaming applications and pipelines that power digital customer experiences and software-driven business operations across your organization.
Fortunately, as Forrester has determined, Confluent’s cloud-native, complete, and fully managed service—with built-in connectors, security and data governance, stream processing, and global availability for all of your data streaming needs—can bring your business savings and benefits of up to $2.58 million, while freeing your team to focus on efforts that differentiate your business rather than managing the underlying data infrastructure.
And you have the peace of mind of knowing all of this is underpinned by Confluent’s industry leading support and services from the creators of Kafka with over 1 million hours of Kafka experience, which includes operating over 15,000 clusters in Confluent Cloud.
If you’re ready to learn how you can eliminate the burdens and risks of self-supporting Kafka and understand the full benefits your organization can achieve, read the Forrester study and reach out to us to get started today.
Why tackle this all on your own? Your teams have better things to do.
Kevin Chao leads product go-to-market strategy as part of the Product Marketing team at Confluent. Prior to Confluent, he worked as a design engineer at Nvidia and Advanced Micro Devices (AMD), before working at McKinsey to help various B2B tech companies on their product and go-to-market strategies.