Confluent

Overview

Confluent offers a Data Streaming Platform to move data in real time and support operations, analytics, and AI across the enterprise. The platform is positioned as the “central nervous system” for organizations, connecting applications, systems, and data layers into a single, real-time data fabric. Its core idea is that streaming, connecting, processing, and governing data in motion enables real-time decision making, AI and agent-driven applications, and unified operations and analytics.

Platform capabilities (four core pillars)

• Stream: Real-time data movement across systems and applications.
• Connect: Bridges a growing network of systems, applications, and data sources.
• Process: Real-time data transformation, cleaning, and augmentation as data moves between destinations.
• Govern: Governance features to ensure discoverability, security, compliance, and trust as data is used by multiple applications.

Key technology and open source foundation

• Built on Apache Kafka (originated with the company’s founders at LinkedIn in 2011) and extended with Apache Flink.
• Includes Tableflow, which materializes data streams into open table formats like Apache Iceberg and Delta Lake, enabling analytics engines to query fresh, governed data.
• Confluent Intelligence: a suite of features that delivers real-time data to production AI systems and provides trusted, contextual data for AI agents.

Products and deployment options

• Fully managed, cloud-native SaaS available on all major cloud providers.
• Bring Your Own Cloud (BYOC) option with shared management between Confluent and the customer.
• Enterprise-ready, self-managed offerings.
• Cross-cloud and hybrid deployment support, designed for scalability, elasticity, security, and global connectivity.
• Designed to reduce complexity and cost through a “Shift Left” architecture that moves processing upstream to minimize recomputation and waste.

Strategic positioning and market trends

• Confluence of three trends:
  1. Generative AI and event-driven systems that require fresh, contextual data with low latency.
  2. Real-time, reusable data assets that serve both analytics (data warehouses/lakes) and operational needs, reducing silos.
  3. Mature, enterprise-ready open source technologies (Kafka, Flink, Iceberg, Delta Lake) that support scalable production deployments.
• Emphasizes open source roots as a differentiator and a driver of adoption and ecosystem familiarity among developers and IT teams.
• The platform aims to enable real-time customer experiences and data-driven business operations.

Customer experience and economics

Confluent’s Data Streaming Journey guides customers from experimentation to organization-wide adoption, using a self-service, cloud-first approach to accelerate initial use cases and expand across lines of business, divisions, and geographies. The company highlights cost and efficiency benefits such as reduced infrastructure spend, lower development and operational resources, and minimized downtime and security costs through standardized, enterprise-grade features and a central data streaming backbone. The Shift Left approach is presented as a key productivity and cost-reduction driver for engineering teams.

Business context and transaction (IBM merger)

• On December 7, 2025, Confluent entered into an Agreement and Plan of Merger with International Business Machines Corporation (IBM) and Corvo Merger Sub, Inc. (IBM subsidiary).
• Terms: Each share of Confluent’s Class A and Class B common stock will be canceled and converted into the right to receive $31.00 per share in cash, subject to withholding taxes.
• Timeline and conditions: The merger is expected to close by mid-2026, subject to customary closing conditions and regulatory approvals. Confluent will continue to operate as an independent company until the effective time.
• For additional details, see Note 1, Organization and Description of Business, in Confluent’s Consolidated Financial Statements.