Why real-time data is becoming essential for AI — and why partners should be talking about it

Real-time data streaming has become a strategic priority for many organizations. IBM's acquisition of Confluent brings together enterprise AI and one of the world's leading data streaming platforms, giving organizations a simpler way to connect applications, systems and data across hybrid environments. For partners, it creates new opportunities to lead conversations around AI, analytics, application modernization and cloud. 

What is Confluent?

Confluent is an enterprise data streaming platform built by the original creators of Apache Kafka. While Kafka provides the foundation for moving data in real time, Confluent adds the capabilities organizations need to run production environments at scale. 

Key capabilities include:

• Cloud-native architecture that automatically scales with demand. 
• Managed Apache Flink for processing and transforming streaming data without managing additional infrastructure. 
• 120+ connectors that integrate databases, SaaS applications, data warehouses and lakes. 
• Built-in governance through Schema Registry and Stream Governance to help maintain data quality and compliance. 

Organizations can choose:

Confluent Cloud — A fully managed SaaS platform available across AWS, Microsoft Azure and Google Cloud. 

Confluent Platform — A self-managed solution for on-premises and highly regulated environments. 

Think of Kafka as the engine. Confluent provides the complete enterprise platform around it. 

Why it matters

Supports AI initiatives with better data 

Many AI projects stall because the underlying data is fragmented or outdated. Confluent continuously streams governed data to AI models and intelligent applications, helping improve relevance and responsiveness.

Become part of critical infrastructure 

Once customers establish a streaming platform, it becomes a core component connecting applications, databases and analytics across the business — creating long-term opportunities for expansion and services. 

Expand data and AI conversations 

Data streaming naturally leads to discussions around analytics, cloud modernization, data platforms and IBM's broader Data and AI portfolio. 

How Confluent stands apart

Customers evaluating data streaming platforms often compare several options. 

Compared with open-source Kafka

Confluent removes much of the operational overhead associated with managing Kafka, including scaling, maintenance, security and governance. 

Compared with Amazon MSK

While Amazon MSK provides managed Kafka infrastructure, Confluent adds enterprise capabilities such as managed Flink, Schema Registry, extensive connectors and multi-cloud flexibility. 

Compared with Redpanda

Redpanda focuses on streaming performance. Confluent offers a broader enterprise platform with a larger ecosystem and more mature cloud capabilities.

Compared with cloud-native messaging services

Services such as Amazon Kinesis, Azure Event Hubs and Google Pub/Sub work well with individual cloud ecosystems. Confluent provides greater portability across hybrid and multi-cloud environments while supporting richer governance, processing and AI integration. 

Customer signals to watch for

Confluent is a strong fit when customers:

• Are struggling to manage Kafka internally. 
• Need real-time visibility across operations. 
• Are building AI applications that require continuously updated data. 
• Want to modernize analytics by reducing batch processing. 
• Operate across multiple clouds or hybrid environments. 

Key benefits

• Reduce operational complexity compared to self-managed Kafka.
• Connect systems faster with 120+ pre-built integrations.
• Deliver governed, real-time data for analytics and AI.
• Support hybrid and multi-cloud strategies. 
• Build on a platform designed to evolve alongside enterprise AI initiatives. 

How to start the conversation

Rather than leading with technology, begin with a business challenge. Ask customers about their AI projects, operational bottlenecks or real-time visibility requirements. From there, demonstrate how data streaming can simplify information flow across the organization and support broader modernization goals. 

Arrow can help partners scope opportunities, develop proof-of-value engagements and support customer conversations throughout the sales cycle. 

Why Arrow?

Arrow helps partners accelerate Confluent opportunities with technical expertise, solution design, enablement and demo support. Whether you're exploring a new customer opportunity or expanding an existing IBM engagement, Arrow can help connect Confluent with the broader IBM Data and AI portfolio and guide customers from initial discovery through proof of value. 

Arrow can help partners scope opportunities, develop proof-of-value engagements and support customer conversations throughout the sales cycle. Access your battlecard and start building stronger customer engagements today.