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Save Costs by Replacing Confluent with Redpanda

1. IntroductionCopied!

As real-time data platforms become increasingly central to modern applications, many organizations turn to the Confluent Platform and Confluent Cloud for their Apache Kafka needs. However, these solutions can be costly, especially at scale.

Redpanda emerges as a compelling alternative: it’s a Kafka API-compatible streaming platform with significant performance advantages and a more lightweight architecture. In this article, we’ll explore if and how replacing Confluent with Redpanda can help you save costs while maintaining or even improving your streaming capabilities.

2. Understanding the Cost Structure of ConfluentCopied!

Before diving into how Redpanda can save money, let’s understand where Confluent’s costs accumulate:

  • Confluent Cloud pricing: Charges based on data ingress/egress, partition counts, storage, and network usage.
  • Licensing costs for self-hosted Confluent Platform: Enterprise licensing can be significant, especially if you use premium features.
  • Infrastructure: Confluent’s reliance on Java Virtual Machine (JVM), Zookeeper, and numerous components (like Schema Registry, Control Center) increases resource usage and costs.
  • Operational overhead: Managing upgrades, scaling brokers, and securing multi-node clusters adds further expense.

At scale, these factors can lead to substantial monthly bills—particularly if you’re running in the cloud with high data egress.

3. Introducing RedpandaCopied!

Redpanda is a modern streaming data platform that’s fully compatible with the Kafka API but designed for higher performance and lower resource usage. Key differences include:

  • No JVM: Redpanda is written in C++ (rather than Java) and has a smaller runtime footprint.
  • No Zookeeper: Redpanda uses a Raft-based consensus system internally, simplifying operations and removing a major source of overhead.
  • Single binary architecture: All core functionality—broker, replication, storage—is handled by one binary, minimizing operational complexity.
  • Kafka API-compatible: Most applications that use Kafka clients can switch to Redpanda without code changes.

4. Key Areas of Cost SavingsCopied!

Here’s how Redpanda directly reduces your streaming platform’s costs:

a. InfrastructureCopied!

  • Lower memory and CPU usage: Redpanda’s efficient C++ implementation requires fewer resources compared to JVM-based Confluent brokers.
  • Smaller node count: Without Zookeeper and with faster performance per broker, you can run fewer servers overall.
  • Simplified deployment: Easier containerization and simpler cloud/on-prem deployment.

b. Operations & MaintenanceCopied!

  • No Zookeeper: Managing a Zookeeper ensemble can be complex and expensive. Redpanda’s built-in consensus model eliminates this.
  • Easier upgrades: Single binary upgrades reduce downtime and errors.
  • Fewer moving parts: Simplifies Day 2 operations and monitoring.

c. LicensingCopied!

  • Community vs. Enterprise: Redpanda offers a free Community Edition suitable for many use cases, with optional paid features in Enterprise Edition.
  • No per-partition or usage-based billing: Unlike Confluent Cloud, which can become expensive as your usage grows.

d. Cloud Egress and NetworkingCopied!

  • Flexible deployment: You can run Redpanda on-prem or in your own cloud environment, reducing data egress charges when your consumers/producers are colocated.
  • Lower data movement costs: Avoid paying high egress fees typical in cloud-managed Confluent environments.

5. Migration StrategyCopied!

Migrating from Confluent (Kafka) to Redpanda can be straightforward thanks to Redpanda’s Kafka API compatibility. A typical migration plan might look like:

  • Assess compatibility: Identify critical features and ensure Redpanda supports them (most Kafka features are covered).
  • Testing environment: Set up a Redpanda cluster in parallel to your existing Confluent setup.
  • Dual-write approach: Temporarily write data to both clusters to ensure compatibility and minimize downtime.
  • Topic mirroring: Use tools like MirrorMaker 2 or Confluent Replicator for topic data migration.
  • Phased cutover: Gradually move consumers and producers to Redpanda.
  • Validation and performance testing: Ensure all clients operate as expected before fully decommissioning Confluent.

6. Summary: When Does It Make Sense?Copied!

Switching from Confluent to Redpanda makes sense in several scenarios:

  • You’re cost-sensitive and need to reduce infrastructure or licensing spend.
  • Your team wants to simplify operations by eliminating Zookeeper.
  • You’re working on edge deployments or resource-constrained environments.
  • You want Kafka compatibility without the overhead of JVM-based brokers.

Redpanda’s performance, lower resource footprint, and flexible licensing model make it an attractive choice for many real-time data use cases.

7. Final ThoughtsCopied!

Redpanda offers a modern, cost-efficient alternative to Confluent’s Kafka offerings without sacrificing performance or compatibility. By removing Zookeeper, leveraging a leaner architecture, and providing flexible licensing, Redpanda can help you cut costs and simplify operations—a winning combination for businesses at any scale.

If you’re considering the switch, start with a proof-of-concept environment and see firsthand how much you can save. For more resources and documentation, check out Redpanda’s official guides and migration tools.