CCDAK learner - Confluent Certified Developer for Apache Kafka

Confluent's (NASDAQ:CFLT) stock has done well in latest months on the back of improving sentiment towards growth stocks and relatively strong first quarter results. While growth is still reasonably robust, it is falling and customer additions are soft. Confluent has also not made that much progress towards operating profitability, which in large part is due to high SBC expenses.

Demand Drivers

While the macro environment remains difficult, Confluent continues to be optimistic about its prospects due the TCO advantage of its cloud offering. Confluent believes that this advantage is sustainable due to the deep technical moat that the company has developed over time.

Much of the cost of running Kafka is related to cloud infrastructure, including compute, storage, networking and the tools needed to ensure smooth operations. The personnel responsible for configuring, deploying and managing Kafka is the other major cost component. Kafka is a sought after skill and as a result, knowledgeable personnel are generally well compensated.

Rather than just offering open-source Kafka as a service, Confluent has made a number of innovations which reduce the cost of operating its cloud service. Unlike many open-source cloud offerings, Confluent’s service is capable of multi-tenant operations which allows it to pool customers on shared infrastructure, driving higher utilization. Confluent also provides intelligent tiering of data between memory, local storage and object storage to help reduce storage costs. Confluent also utilizes real-time performance data from customers to optimize the routing of traffic, thereby improving performance and reducing costs. This is a scale-based advantage that is likely to increase over time as Confluent Cloud grows larger.

Confluent is not immune from the macro environment though, which appears to be deteriorating. Planned technology expenditures continue to decline, which is suggestive of a further moderation in growth for Confluent. While investors may be expecting AI to reverse this trend, the impact of generative AI in the near-term is likely to be more narrow than many expect. There is also significant danger extrapolating the latest surge in interest caused by LLMs. While LLMs and tools like Copilot are likely to be important long-term, they are probably overhyped at the moment. Confluent is also unlikely to be a significant direct beneficiary from AI, despite forming a critical part of modern data stacks. Confluent’s management team has suggested that they could benefit by providing LLMs with access to fresh data, but the incremental demand from this may be small relative to their existing business.

Financial Analysis

Confluent Cloud continues to drive Confluent's growth, increasing by 89% YoY in the first quarter. Confluent's international business was also an area of strength, with revenue outside of the US increasing by 49% YoY. Europe's recovery from the initial impact of the war in Ukraine and Asia fully emerging from the pandemic are possible tailwinds at the moment. Growth in RPO was impacted by a decline in average contract duration during the first quarter, along with longer deal cycles and a tough comparable period in 2022.

Revenue growth in the second quarter and for the full year is expected to be 30-31% YoY. Confluent's revenue growth continues to decelerate, but this has not been as severe as many peers, which may have contributed to share price strength in latest months.

Confluent’s gross retention rate remains above 90%, which should in theory lead to decent profit margins in time. Confluent’s position as a connector between applications also means lock-in could increase over time as the number of applications relying on the service increases.

Net retention continued to be strong in the first quarter, although net new customers moderated somewhat. The number of large customers (>100,000 USD ARR) increased by 34% YoY, indicating strength amongst larger organizations. Large customers were responsible for 85% of Confluent’s revenue in the first quarter. The number of customers with more than 1 million USD ARR increased by 53% YoY.

Confluent's growth is in large part driven by increasing consumption, and providing the underlying activity of customer applications remains strong, growth should not deteriorate too much.

The number of job openings mentioning Confluent in the job requirements has trended downward over the past 12 months, which broadly reflects the slowdown in customer additions.

Growth in search interest for "Confluent Pricing" has also begun to moderate in latest months. This seems to align with other indicators of a softer demand environment.

Confluent’s subscription gross margins continue to deteriorate as the cloud business grows in importance. Management has stated that unit economics of the cloud offering continue to Boost though. It is unclear whether gross profit margins have already bottomed, but they are now broadly in line with management's long-term target.

Confluent continues to focus on improving non-GAAP operating margins, but the company’s GAAP margins continue to be extremely poor. Sales and marketing expenses are high, and are yet to moderate, even with a substantial fall in growth. Investors should look for Confluent’s restructuring and more modest hiring to begin yielding benefits in the second half of the year.

Job openings at Confluent have rebounded significantly in latest months, but now appear to have stabilized. This could suggest that the macro environment has deteriorated somewhat post SVB.

Valuation

The market continues to place a high weight on profitability relative to growth, which has been an important driver of Confluent's stock price over the past 12 months. After the latest increase in price, the stock appears to be valued broadly in line with peers given the company's growth rate, but the stock could fall again if growth continues to deteriorate.

Digital leaders who want to explore the benefits of Confluent Cloud should find a strong business case and engage with experts inside and outside the organization.

That’s the conclusion of three IT professionals, who told diginomica at the recent Kafka Summit London in London how their businesses implemented cloud-based technology from Confluent, which is a commercial provider of the open-source Apache Kafka movement. 

For those interested in exploring the Confluent Cloud, there are three key take-away lessons: work with specialist support, get stakeholder buy-in, and focus on education.

Work with specialist support

Michael Holste, System Architect at Deutsche Post DHL, says his team started investigating how it could Boost an internal system that distributes shipping-event data for the distribution of parcels across Germany two years ago. The system transported about 170 million messages per day and 5,000 messages per second at peak. However, the system was based on legacy technology and couldn’t be scaled upwards, he explains: 

We knew we needed to have another solution for message transport. So, we focused on Apache Kafka, and especially Confluent. We had support from Confluent. We had an architect who helped us design the solution. He was very helpful because he had deep insight into all specialities of Apache Kafka that we couldn't see.

At first, Deutsche Post DHL ran the new system on-premises in a data center in Frankfurt. About one and a half years ago, they established two clusters in the Azure cloud. Now, Confluent is hosted in the cloud and the company is transferring 200 million messages per day online. He says the business has about 50 systems that deliver data and another 50 that consume it. Rather than queuing data, Confluent keeps the business up to date on a range of concerns – from distribution to sorting – and allows people to self-serve, says Holste:

It works fine. It was a huge effort to switch from queues to topics, because now the users have to decide themselves what they need and what they want, so it was big mind shift. It was really helpful to have the support of Confluent at that point because we wouldn't have been able to support that mind shift.

Deutsche Post DHL is now thinking about how to use the cluster for other purposes, such as master data management. The aim will be to create a data mesh that helps distribute insight to all parts of the company. When it comes to best-practice techniques, Holste says other digital leaders should create a tight, structured approach:

Have the support of an architect at Confluent. He helped people to change their mindsets and see things they didn't see before. It’s also important to be sure of what you want to do with the technology.

Get stakeholder buy-in

Paul Makkar, Global Director of the Datahub at Saxo Bank, says his firm operates a single, hybrid on-premises stack based in Copenhagen. The bank pushes about $20 billion in transactions a day and offers 70,000 trading instruments to institutional, white-label and retail clients. However, Saxo had challenges around scaling and wanted to take advantage of the cloud, so turned to Kafka and Confluent. Makkar recalls: 

We wanted to create a self-service, easy-to-consume platform for domain teams. We don't want to be the guys in the middle, telling them how to do stuff in intricate detail. We wanted to give them what they need in terms of connectors and syllabus and to organize that by domain team. We have a series of back-end processes that mean they can self-serve what they actually need through a cluster.

With stakeholder buy-in, Saxo is developing a data mesh-like approach to data. The adoption of Confluent Cloud pre-dated Makkar’s arrival at the firm two and a half years ago, but he was in situ when the contract came up for renewal. He says there weren’t any other competitors that provided a similar all-in-one-solution:

The reality of Kafka is that it sits in a world where people aren't going to adopt it by just suddenly switching over to be completely event driven. You will always need to integrate some databases – and Confluent is really the only show in town.

Makkar advises other digital and business leaders who are thinking of using Confluent to get high-level stakeholder buy-in and to find a path that makes sense for the organization: 

You might move slowly, take your learnings, and get engagement and interest going. When technical and domain teams see success with new technology, they’re hurry to understand more. But I think it's really hard, especially with critical systems, to do what we've done unless you've got high-level buy-in.

Focus on education

Gustavo Ferreira, Tech Lead Software Engineer at financial services specialist Curve, says his organization was previously using the open-source message-broker RabbitMQ, but was spending too much time maintaining the self-managed system. Two years ago, they started exploring solutions to their architectural challenges before selecting Kafka. Ferreira says:

It’s log-based, so it opens up new patterns and opportunities that you wouldn't have with other technologies. Also, there’s a huge community, so you have more people thinking about the same problems and how to solve them with technology. You also have connectors with Kafka, which allows you to move data from one store to another. And that for us was very important because we wanted to do streaming.

After deciding to go with Kafka, Curve opted for Confluent’s fully managed solution as the team wanted to deliver the most value with the least resources. One of the principal engineers had worked with Confluent before and was impressed, adds Ferreira: 

And after two years of being with Confluent, we've never had an incident and the support is excellent. You can go very high level and very deep. Support is like insurance. You don't usually need it. But when you need it, it's there and they can help you – and it doesn't matter how deep the problem, you’re going to have someone that can help.

Today, Ferreira says the combination of Kafka and Confluent Cloud is helping the business reach its desired destination, suggesting it’s “the backbone” of all asynchronous communications. For other digital leaders who want to take a similar route, he says teams need to know how to make the most of the benefits that Kafka and Confluent provide:

If you are serious about having a new technology in your company, you need to have a group of two or three people – even if it's a temporary team – where they are focused on learning the technology and integrating it with other systems.

Confluent has announced several new Confluent Cloud capabilities and features that address the data governance, security, and optimization needs of data streaming in the cloud.

“Real-time data is the lifeblood of every organization, but it’s extremely challenging to manage data coming from different sources in real time and certain that it’s trustworthy,” said Shaun Clowes, chief product officer at Confluent, in a release. “As a result, many organizations build a patchwork of solutions plagued with silos and business inefficiencies. Confluent Cloud’s new capabilities fix these issues by providing an easy path to ensuring trusted data can be shared with the right people in the right formats.”

Confluent’s 2023 Data Streaming Report, also newly released, found that 72% of IT leaders cite the inconsistent use of integration methods and standards as a challenge or major hurdle to their data streaming infrastructure, a problem that led the company to develop these new features.

A New Engine

Right off the bat, the engine powering Confluent Cloud has been reinvented. Confluent says it has spent over 5 million engineering hours to deliver Kora, a new Kafka engine built for the cloud.

(Source: Confluent)

Confluent Co-founder and CEO Jay Kreps penned a blog post explaining how Kora came to be: “When we launched Confluent Cloud in 2017, we had a grand vision for what it would mean to offer Kafka in the cloud. But despite the work we put into it, our early Kafka offering was far from that—it was basically just open source Kafka on a Kubernetes-based control plane with simplistic billing, observability, and operational controls. It was the best Kafka offering of its day, but still far from what we envisioned.”

Kreps goes on to say that the challenges facing a cloud data system are different from a self-managed open source download, such as the need for scalability, security, and multi-tenancy. Kora was designed with these constraints in mind, Kreps says, as it is multi-tenant first, can be run across over 85 regions in three clouds, and is operated at scale by a small on-call team. Kora disaggregates individual components within the network, compute, metadata, and storage layer, and data locality can be managed between memory, SSDs, and object storage. It is optimized for the cloud environment and the particular workloads of a streaming system in the cloud, and real-time usage is captured to Boost operations like data placement and fault detection and recovery, as well as costs for large-scale use.

Krebs says Kora will not displace open source Kafka and the company will continue contributing to the project. Kora is 100% compatible with all currently supported versions of the Kafka protocol. Check out his blog for more details.

(pichetw/Shutterstock)

Data Quality Rules

Data Quality Rules is a new feature in Confluent’s Stream Governance suite that is geared towards the governance of data contracts. Confluent notes that a critical component of data contracts enforcement is the rules or policies that ensure data streams are high-quality, fit for consumption, and resilient to schema evolution over time. The company says it is addressing the need for more comprehensive data contracts with this new feature, and schemas stored in Schema Registry can now be augmented with several types of rules. With Data Quality Rules, values of individual fields within a data stream can be validated and constrained to ensure data quality, and if data quality issues arise, there are customizable follow-up actions on incompatible messages. Schema evolution can be simplified using migration rules to transform messages from one data format to another, according to Confluent.

“High levels of data quality and trust improves business outcomes, and this is especially important for data streaming where analytics, decisions, and actions are triggered in real time,” said Stewart Bond, VP of data intelligence and integration software at IDC said in a statement. “We found that customer satisfaction benefits the most from high quality data. And, when there is a lack of trust caused by low quality data, operational costs are hit the hardest. Capabilities like Data Quality Rules help organizations ensure data streams can be trusted by validating their integrity and quickly resolving quality issues.”

Custom Connectors

Instead of relying on self-managed custom-built connectors that require manual provisioning, upgrading, and monitoring, Confluent is now offering Custom Connectors to enable any Kafka connector to run on Confluent Cloud without infrastructure management. Teams can connect to any data system using their own Kafka Connect plugins without code changes, and there are built-in observability tools to monitor the health of the connectors. The new Custom Connectors are available on AWS in select regions with support for additional regions and cloud providers coming soon.

“To provide accurate and current data across the Trimble Platform, it requires streaming data pipelines that connect our internal services and data systems across the globe,” said Graham Garvin, product manager at Trimble. “Custom Connectors will allow us to quickly bridge our in-house event service and Kafka without setting up and managing the underlying connector infrastructure. We will be able to easily upload our custom-built connectors to seamlessly stream data into Confluent and shift our focus to higher-value activities.”

Stream Sharing

Confluent’s Stream Sharing allows syllabus in Kafka to be shared. (Source: Confluent)

For organizations that exchange real-time data internally and externally, relying on flat file transmissions or polling APIs for data exchange could result in security risks, data delays, and integrations complexity, Confluent asserts. Stream Sharing is a new feature that allows users to exchange real-time data directly from Confluent to any Kafka client with security capabilities like authenticated sharing, access management, and layered encryption controls.

In Kafka, a syllabu is a category or feed that stores messages where producers write data to syllabus and consumers retrieve it through messages. Stream Sharing allows users to share syllabus outside of their Confluent Cloud organization between enterprises, and invited consumers can stream shared syllabus with an existing log-in or a new account using a Kafka client.

Early Access for Managed Apache Flink

Confluent is also debuting is a new early access program. Apache Flink is often chosen by customers for querying large-scale, high throughput data streams, and it operates as a service at the cloud layer. Confluent recently acquired Immerok, developer of a cloud-native and fully managed Flink service for large-scale data stream processing. At the time of the acquisition, Confluent announced it had plans to launch its own fully managed Flink service compatible with Confluent Cloud. The time has come: Confluent has opened an early access program for managed Apache Flink to select Confluent Cloud customers. The company says this program will allow customers to try the service and help shape the roadmap by partnering with the company’s product and engineering teams.

For a full rundown of Confluent’s news, check out Jay Kreps’ keynote from May 16 at Kafka Summit London 2023 here.

Related Items:

Confluent Works to Hide Streaming Complexity

Confluent Delivers New Cluster Controls, Data Connectors for Hosted Kafka

Confluent to Develop Apache Flink Offering with Acquisition of Immerok

MOUNTAIN VIEW, Calif., May 16, 2023--(BUSINESS WIRE)--Confluent, Inc. (NASDAQ: CFLT), the data streaming pioneer, today announced that its management will present at the following upcoming investor conferences:

J.P. Morgan Global Technology, Media & Communications Conference
Date: Tuesday, May 23, 2023
Time: 7:50 a.m. PT / 10:50 a.m. ET

William Blair Annual Growth Stock Conference
Date: Tuesday, June 6, 2023
Time: 6:00 a.m. PT / 9:00 a.m. ET

A live webcast and a replay of each presentation will be available on Confluent’s investor relations website at investors.confluent.io.

About Confluent
Confluent is the data streaming platform that is pioneering a fundamentally new category of data infrastructure that sets data in motion. Confluent’s cloud-native offering is the foundational platform for data in motion – designed to be the intelligent connective tissue enabling real-time data, from multiple sources, to constantly stream across the organization. With Confluent, organizations can meet the new business imperative of delivering rich, digital front-end customer experiences and transitioning to sophisticated, real-time, software-driven backend operations.

View source version on businesswire.com: https://www.businesswire.com/news/home/20230515005885/en/

Contacts

Investor Contact
Shane Xie
investors@confluent.io

Media Contact
Taylor Jones
pr@confluent.io

New Confluent Features Make It Easier and Faster to Connect, Process, and Share Trusted Data, Everywhere

Data Quality Rules, part of the first fully managed governance solution for Apache Kafka, helps teams enforce data integrity and quickly resolve data quality issues

Confluent announces Custom Connectors and Stream Sharing, making connecting custom applications and sharing real-time data internally and externally effortless

Confluent’s Kora Engine powers Confluent Cloud to deliver faster performance and lower latency than open source Apache Kafka

Confluent’s Apache Flink early access program opens to select customers to help shape the product roadmap

Confluent, Inc. (NASDAQ: CFLT), the data streaming pioneer, today announced new Confluent Cloud capabilities that give customers confidence that their data is trustworthy and can be easily processed and securely shared. With Data Quality Rules, an expansion of the Stream Governance suite, organizations can easily resolve data quality issues so data can be relied on for making business-critical decisions. In addition, Confluent’s new Custom Connectors, Stream Sharing, the Kora Engine, and early access program for managed Apache Flink make it easier for companies to gain insights from their data on one platform, reducing operational burdens and ensuring industry-leading performance.

“Real-time data is the lifeblood of every organization, but it’s extremely challenging to manage data coming from different sources in real time and certain that it’s trustworthy,” said Shaun Clowes, Chief Product Officer at Confluent. “As a result, many organizations build a patchwork of solutions plagued with silos and business inefficiencies. Confluent Cloud’s new capabilities fix these issues by providing an easy path to ensuring trusted data can be shared with the right people in the right formats.”

Having high-quality data that can be quickly shared between teams, customers, and partners helps businesses make decisions faster. However, this is a challenge many companies face when dealing with highly distributed open source infrastructure like Apache Kafka. According to Confluent’s new 2023 Data Streaming Report, 72% of IT leaders cite the inconsistent use of integration methods and standards as a challenge or major hurdle to their data streaming infrastructure. Today’s announcement addresses these challenges with the following capabilities:

Data Quality Rules bolsters Confluent’s Stream Governance suite to further ensure trustworthy data

Data contracts are formal agreements between upstream and downstream components around the structure and semantics of data that is in motion. One critical component of enforcing data contracts is rules or policies that ensure data streams are high-quality, fit for consumption, and resilient to schema evolution over time.

To address the need for more comprehensive data contracts, Confluent’s Data Quality Rules, a new feature in Stream Governance, enable organizations to deliver trusted, high-quality data streams across the organization using customizable rules that ensure data integrity and compatibility. With Data Quality Rules, schemas stored in Schema Registry can now be augmented with several types of rules so teams can:

• Ensure high data integrity by validating and constraining the values of individual fields within a data stream.
• Quickly resolve data quality issues with customizable follow-up actions on incompatible messages.
• Simplify schema evolution using migration rules to transform messages from one data format to another.

“High levels of data quality and trust improves business outcomes, and this is especially important for data streaming where analytics, decisions, and actions are triggered in real time,” said Stewart Bond, VP of Data Intelligence and Integration Software at IDC. “We found that customer satisfaction benefits the most from high quality data. And, when there is a lack of trust caused by low quality data, operational costs are hit the hardest. Capabilities like Data Quality Rules help organizations ensure data streams can be trusted by validating their integrity and quickly resolving quality issues.”

Custom Connectors enable any Kafka connector to run on Confluent Cloud without infrastructure management

Many organizations have unique data architectures and need to build their own connectors to integrate their homegrown data systems and custom applications to Apache Kafka. However, these custom-built connectors then need to be self-managed, requiring manual provisioning, upgrading, and monitoring, taking away valuable time and resources from other business-critical activities. By expanding Confluent’s Connector ecosystem, Custom Connectors allow teams to:

• Quickly connect to any data system using the team’s own Kafka Connect plugins without code changes.
• Ensure high availability and performance using logs and metrics to monitor the health of team’s connectors and workers.
• Eliminate the operational burden of provisioning and perpetually managing low-level connector infrastructure.

“To provide accurate and current data across the Trimble Platform, it requires streaming data pipelines that connect our internal services and data systems across the globe,” said Graham Garvin, Product Manager at Trimble. “Custom Connectors will allow us to quickly bridge our in-house event service and Kafka without setting up and managing the underlying connector infrastructure. We will be able to easily upload our custom-built connectors to seamlessly stream data into Confluent and shift our focus to higher-value activities.”

Confluent’s new Custom Connectors are available on AWS in select regions. Support for additional regions and other cloud providers will be available in the future.

Stream Sharing facilitates easy data sharing with enterprise-grade security

No organization exists in isolation. For businesses doing activities such as inventory management, deliveries, and financial trading, they need to constantly exchange real-time data internally and externally across their ecosystem to make informed decisions, build seamless customer experiences, and Boost operations. Today, many organizations still rely on flat file transmissions or polling APIs for data exchange, resulting in data delays, security risks, and extra integration complexities. Confluent’s Stream Sharing provides the easiest and safest alternative to share streaming data across organizations. Using Stream Sharing, teams can:

• Easily exchange real-time data without delays directly from Confluent to any Kafka client.
• Safely share and protect your data with robust authenticated sharing, access management, and layered encryption controls.
• Trust the quality and compatibility of shared data by enforcing consistent schemas across users, teams, and organizations.

Additional innovations to be announced at Kafka Summit London:

Organized by Confluent, Kafka Summit London is the premier event for developers, architects, data engineers, DevOps professionals, and those looking to learn more about streaming data and Apache Kafka. This event focuses on best practices, how to build next-generation systems, and what the future of streaming technologies will be.

Other new innovations in Confluent’s leading data streaming platform include:

• Kora powers Confluent Cloud to deliver faster insights and experiences: Since 2018, Confluent has spent over 5 million engineering hours to deliver Kora, an Apache Kafka engine built for the cloud. With its multi-tenancy and serverless abstraction, decoupled networking-storage-compute layers, automated operations, and global availability, Kora enables Confluent Cloud customers to scale 30x faster, store data with no retention limits, protect them with a 99.99% SLA, and power workloads with low latency.
• Confluent’s Apache Flink early access program previews advanced stream processing capabilities: Stream processing plays a critical role in data streaming infrastructure by filtering, joining, and aggregating data in real time, enabling downstream applications and systems to deliver instant insights. Customers are turning to Flink to handle large-scale, high throughput, and low latency data streams with its advanced stream processing capabilities and robust developer communities. Following Confluent’s Immerok acquisition, the early access program for managed Apache Flink has opened to select Confluent Cloud customers to try the service and help shape the roadmap by partnering with the company’s product and engineering teams.

Connect with Confluent at Kafka Summit London to learn more!

Learn more about these new features at Kafka Summit London! Register here to watch the keynote presentation by Confluent’s CEO and cofounder Jay Kreps about the future of stream processing with Apache Flink today, May 16 at 10 am BST.

Additional Resources

• Explore all the new innovations of the Confluent Q2 ‘23 Launch in this blog post
• Learn more about Confluent’s Kora engine
• For deep dives into each feature, register for the upcoming Confluent Q2 ‘23 Launch webinar
• See how Confluent is helping customers transform their businesses
• Join Confluent—apply for an open position

About Confluent

Confluent is the data streaming platform that is pioneering a fundamentally new category of data infrastructure that sets data in motion. Confluent’s cloud-native offering is the foundational platform for data in motion—designed to be the intelligent connective tissue enabling real-time data, from multiple sources, to constantly stream across the organization. With Confluent, organizations can meet the new business imperative of delivering rich, digital front-end customer experiences and transitioning to sophisticated, real-time, software-driven back-end operations. To learn more, please visit www.confluent.io.

Confluent and associated marks are trademarks or registered trademarks of Confluent, Inc.

Apache® and Apache Kafka® are either registered trademarks or trademarks of the Apache Software Foundation in the United States and/or other countries. No endorsement by the Apache Software Foundation is implied by the use of these marks. All other trademarks are the property of their respective owners.

This press release contains forward-looking statements. The words “believe,” “may,” “will,” “ahead,” “estimate,” “continue,” “anticipate,” “intend,” “expect,” “seek,” “plan,” “project,” and similar expressions are intended to identify forward-looking statements. These forward-looking statements are subject to risks, uncertainties, and assumptions. If the risks materialize or assumptions prove incorrect, genuine results could differ materially from the results implied by these forward-looking statements. Confluent assumes no obligation to and does not currently intend to, update any such forward-looking statements after the date of this release.

Natalie Mangan
pr@confluent.io

View source version on businesswire.com: https://www.businesswire.com/news/home/20230516005397/en/

• Confluent is relatively well placed in the long run as it does not face the direct competition that many SaaS companies do.
• Confluent's value proposition appeals to larger organizations, which could be a headwind in the near term, but also provides a large opportunity.
• Margins continue to be a problem for Confluent, in large part due to SBC. The company is inefficient and has demonstrated limited ability to Boost margins with scale.

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