Sácale el máximo partido a los datos para tus

Confluent, powered by our cloud-native Apache Kafka and Apache Flink services, supports a vast array of real-time use cases by acting as the central nervous system for a business's data. With Confluent, you can:

• Build real-time data pipelines for continuous change data capture, log aggregation, and extract-transform-load processing.
• Power event-driven architectures to coordinate communication across your microservice applications, customer data landscape, and IoT platforms.
• Feed analytics engines and AI systems the data they need to detect anomalies and prevent fraud, accelerate business intelligence and decision-making, and process user activity to deliver personalized outreach, service, and customer support.

From highly regulated financial services and public sector organizations to fast-paced tech startups, Confluent provides the real-time data infrastructure that enables innovation and industry-specific differentiation. Confluent’s 5,000+ customers span banking, insurance, retail, ecommerce, manufacturing, healthcare and beyond. Here are some examples of how Confluent has helped these organizations succeed:

• Banking: Enables instant fraud detection, real-time risk management, and modernization of core banking systems at companies like Capital One, Citizens Bank, and Evo Banco.
• Retail & eCommerce: Creates seamless, personalized omnichannel experiences and optimizes complex supply chain logistics for companies like Walmart and Victoria’s Secret.
• Manufacturing: Powers smart factories by processing IoT sensor data for predictive maintenance and quality control for L'Oréal, BMW Group, Siemens Healthineers, and more.
• Telecommunications: Monitors massive volumes of network data to ensure service quality and enables real-time billing and customer service.

A data product is a reusable, discoverable, and trustworthy data asset, delivered as a product. In the context of data in motion, a data product is typically a well-defined, governed, and reliable event stream. It has a clear owner, a defined schema, documented semantics, and quality guarantees (SLAs), making it easy for other teams to discover and consume.

Confluent enables the creation and management of universal data products through its Stream Governance suite, allowing organizations to prevent data quality issues and enrich data closer to the source so streams can be shared and consumed across the business to accelerate innovation.

• Event-Driven Microservices: Confluent acts as the asynchronous communication backbone. Instead of making direct, synchronous calls to each other (which creates tight coupling and brittleness), services produce events to Kafka topics (e.g., OrderCreated). Other interested services subscribe to these topics to react to the event. This decouples services, allowing them to be developed, deployed, and scaled independently.
• Generative AI: Generative AI models provide powerful reasoning capabilities but lack long-term memory and real-time context. Confluent bridges this gap by feeding AI applications with fresh, contextual data in motion.
• Data Pipelines: Confluent is the core of a modern, real-time data pipeline.
• Ingest: Kafka Connect sources data from databases, applications, and SaaS platforms in real time.
• Process: Data can be processed in-flight using Kafka Streams or Flink to filter, enrich, or aggregate it.
• Egress: Kafka Connect then sinks the processed data into target systems like data lakes, warehouses, or analytics tools for immediate use.

Confluent’s library of reference architectures provides proven, repeatable blueprints for implementing common solutions with experts at Confluent and from across our partner ecosystem. These architectures are critical for successful solution delivery because they:

• Accelerate Time-to-Value: They provide a validated starting point, eliminating the need for teams to design common patterns from scratch
• Reduce Risk: Architectures are based on best practices learned from hundreds of successful customer deployments, covering aspects like security, scalability, data governance, and operational resilience.
• Ensure Best Practices: They guide developers and architects on how to use Confluent features (like Kafka, ksqlDB, Connect, and Schema Registry) correctly and efficiently for a specific use case
• Provide a Common Language: They give technical teams, business stakeholders, and Confluent experts a shared understanding of the solution's design and goals.

Enterprises choose a deployment model based on their operational preferences, cloud strategy, and management overhead requirements.

• Fully Managed on AWS, Microsoft Azure, or Google Cloud: Confluent Cloud is the simplest, fastest, and most cost-effective way to get started, as Confluent handles all the provisioning, management, scaling, and security of the Kafka cluster.
• Self-Managed On-Premises or in the Cloud: Confluent Platform is a self-managed software package that enterprises can deploy and operate on their own infrastructure, whether in a private data center or a private cloud. This model offers maximum control and customization but requires the enterprise to manage the operational overhead.
• BYOC—The Best of Self-Managed and Cloud Services: With WarpStream by Confluent, you can adopt the Bring Your Own Cloud (BYOC) deployment model to combine the ease of use of a managed Kafka service with the cost savings and data sovereignty of a self-managed environment.
• Hybrid Cloud Deployments: This is a very common model where Confluent Cloud is used as the central data plane, but it connects to applications and data systems running in on-premises data centers. Confluent's Cluster Linking feature seamlessly and securely bridges these environments, allowing data to flow bi-directionally without complex tooling.

Confluent excels at integration because of it’s robust, flexible portfolio of pre-built connectors, which you can explore on Confluent Hub.

Kafka Connect is the primary framework for integrating Kafka workloads with external systems—it allows for streaming data between Kafka and other systems without writing custom code. Confluent provides a library of 120+ pre-built connectors for virtually any common data system, including:

• Databases: Oracle, PostgreSQL, MongoDB, SQL Server
• Data Warehouses: Snowflake, Google BigQuery, Amazon Redshift
• Cloud Storage: Amazon S3, Google Cloud Storage, Azure Blob Storage
• SaaS Applications: Salesforce, ServiceNow

Organizations that adopt Confluent should expect tangible business value, not just technical improvements.

• Boost Operational Efficiency: Automate manual data integration processes and break down data silos, freeing up engineering resources to focus on innovation instead of maintaining brittle data pipelines while decreasing the cost of self-managing Kafka.
• Elevate Customer Experience: Move from batch-based personalization to real-time interactions. Deliver instant notifications, personalized recommendations, and immediate customer support based on the latest user activity.
• Drive New Revenue Streams: Create entirely new data-driven products and services, including through Confluent’s OEM Program for cloud and managed service providers (CSPs, MSPs) and independent software vendors (ISVs). For example, a logistics company can sell a real-time shipment tracking API, a bank can offer instant payment confirmation services, or a service provider could offer data streaming-as-a-service to customers already using them as part of their technology stack.
• Mitigate Risk and Fraud: Reduce financial losses by detecting and stopping fraudulent transactions in milliseconds, before the damage is done. Proactively identify security threats by analyzing user behavior and system logs in real time.
• Increase Business Agility: Empower development teams to build and launch new applications and features faster by using a decoupled, event-driven architecture.

The easiest entry point is the fully managed service. You can sign up for a free trial that includes $400 in free usage credits to build your first proof-of-concept. From there:

• Visit Confluent Developer, which has introductory, intermediate, and advanced courses that will guide you through fundamentals, product and feature capabilities, and best practices.
• Identify a Pilot Project: Choose a high-impact but low-risk initial use case. A great first project is often streaming change data from a single database to a cloud data warehouse like Snowflake or BigQuery.
• Use Pre-Built Connectors: Leverage the fully managed connectors in Confluent Cloud to connect to your existing systems in minutes with just a few configuration steps—no custom code required.
• Scale and Govern: Once your pilot is successful, use Confluent's governance tools to turn your data streams into reusable data products and expand to more critical use cases.
• Contact Our Product Experts: Have questions about your use case, migrating to Confluent, or costs for enterprise organizations? Reach out to our team so they can provide answers personalized to your specific requirements and architecture.

Confluent provides a comprehensive ecosystem to ensure customer success at every stage of adoption including:

• Our Partner Ecosystem: A global network of technology partners and system integrators (SIs) who are trained and certified to design, build, and deliver solutions on the Confluent platform.
• Confluent Support: Offers tiered technical support plans (Developer, Business, Premier) with guaranteed SLAs, providing access to a global team of Apache Kafka and Confluent experts to help with troubleshooting and operational issues.
• Confluent Professional Services: A team of expert consultants who can help with:
• Architecture and Design: Validating your architecture and providing best-practice guidance.
• Implementation Assistance: Hands-on help to accelerate your first project.
• Health Checks & Optimization: Reviewing existing deployments to ensure they are secure, performant, and scalable.
• Confluent Education: Provides in-depth training courses and certifications for developers, administrators, and architects to build deep expertise in Kafka and Confluent.