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Modernize Messaging Workloads to Move Beyond Queues and Pub/Sub
Simplify real-time data movement and set data in motion with a modern messaging platform. Avoid the headaches from data coupling and a lack of fault tolerance at scale with legacy messaging middleware. Augment and modernize your existing middleware with an elastically scalable and future-proof platform, engineered for the Cloud.
Challenges with legacy middleware
Traditional messaging systems like Message Queues (MQs), Enterprise Service Buses (ESBs), and Extract, Transform and Load (ETL) tools have been widely used for decades to handle message distribution and inter-service communication across distributed applications. However, they can no longer keep up with the needs of modern applications across hybrid and multi cloud environments for asynchronicity, heterogeneous datasets and high volume throughput.
Designed as monolithic systems, they are riddled with many challenges: they lack persistence or the ability to efficiently handle highly scalable, efficient and reliable message delivery. They don’t handle the real-time interactions and in-flight stream processing that modern applications demand.
This has left organizations with significant technical debt, demanding the need for a modern approach to messaging middleware.
How Confluent Can Help
Confluent provides a future-proof platform, built on Apache Kafka, to stream data across hybrid and multi-cloud environments. It's infinitely scalable on-demand and is a persistent system of record. Remove operational complexity with a decoupled event-driven infrastructure so your developers can focus on building business logic faster with a rich ecosystem of connectors and sophisticated stream processing capabilities. Migrate at your own pace to a cloud-first architecture.
Build a Modern Architecture
Transform your infrastructure to enable real-time workloads and applications. Develop new use cases with a fast time to market in days, not months.
Achieve any Scale
Future-proof your data architecture to maintain high availability and performance at elastic scale. Our customers routinely use Confluent to Handle 10 Trillion+ Messages Per Day.
Migrate with Ease
Start unlocking legacy data for new hybrid and multi cloud use-cases and easily migrate existing messaging workloads, at your own pace.
Reduce Messaging TCO and Technical Debt
Cut 40-70% of your messaging costs and eliminate technical debt. Future-proof your data architecture with a cloud-ready solution.
Why Confluent
Fully decouple, standardize and govern data across your systems
Schema Registry allows for a common way to share clean and governed data between producers and consumers, even as your schemas evolve over time. A rich ecosystem of 120+ connectors allows you to connect IBM MQ, TIBCO, HiveMQ, RabbitMQ and ActiveMQ to third party consumer applications (Snowflake, MongoDB).
Launch new real-time applications, within days with native stream APIs
Take advantage of Kafka-native stream APIs or Flink, especially for real-time data processing, complex event processing, or applications requiring stateful operations and windowing.
Design a persistent system of record with in-order replay and design contextual stateful applications
Tiered Storage makes storing huge volumes of data in Kafka manageable by reducing operational burden and cost. Event Sourcing easily recreates materalized views. Exactly-once semantics guarantees all messages will always be delivered exactly once. Stateful applications eliminate performance impacts from additional queries to databases.
Leverage a fault-tolerant platform at elastic scale
Ensure the highest levels of availability and reliability with Cluster Linking for multi-zone and multi-region data backups. Monitor the health of your clusters, topics, and consumers in Confluent Control Center. Role-based access control (RBAC) provides multi-tenancy and enterprise scaling on a common infrastructure.
Eliminate slowdown and outages due to slow or offline consumers
Topic partitions provide high performance, scalable and deterministic persistence. Self-Balancing Clusters and Tiered Storage deliver fully automated load balancing. Confluent for Kubernetes simplifies deployment and operations, utilizing our packaged best practices to run a secure, reliable, and production-ready data-in-motion platform.
Modernize workloads incrementally over time, to reduce TCO and operational complexity
With support for traditional messaging patterns (Point-to-point and Publish/Subscribe routing semantics) in Confluent, migrate at your own pace without business disruption. Leverage a rich connector ecosystem and applications that natively have Kafka built-in. With Usage based billing, you only pay for what you use.
Ready to get started?
Getting started is easy. Sign up today for a live demo or check out one of our whitepapers on this topic.
Top 6 reasons to Modernize Legacy Middleware
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Compare Confluent to Traditional Middleware
Messaging Integration with Confluent
Why Customers Love Confluent
Nord/LB
"Confluent is enabling us to address our need for a scalable, highly available messaging infrastructure that allows us to decouple our producers from consumers, setting the stage for us to be more flexible, agile, and responsive to change."
Sven Wilbert, Data Manager, NORD/LB
Additional Resources
Here are related resources to help you learn more about messaging systems, real-time data streaming and analytics, event processing, and how Confluent works
Blogs and Case Studies
- Messaging Modernization with Confluent
- Messaging as the Single Source of Truth
- Benchmarking Messaging Systems - Which is Fastest?
- Learn about the benefits of an event-driven architecture
- Amyway accelerates messaging modernization with Confluent
- Rodan+Fields is moving from batch-oriented to data in motion paradigm with Confluent
Webinars and Documentation
- Webinar: Modernize Your Messaging Workloads with Data Streaming
- Webinar: How UC San Diego Transformed the University System Through Real-Time Data?
- Webinar: Putting the Right Parts in Place: Enabling an Enterprise Transformation with Real-Time Data at Advance Auto Parts
- What is Confluent Cloud?
- Kafka Streams Developer Guide
- Building Data Pipelines