Redpanda 25.3 delivers near-instant disaster recovery, and more

If you run real‑time systems, you’re juggling three challenges at once: risk, cost, and complexity. Redpanda 25.3 is coming soon with features that help address all three:

• Cluster shadowing for enterprise-grade resiliency and disaster recovery
• Cloud Topics for cost-efficient observability and analytics workloads
• Google BigLake support for Iceberg Topics lakehouse governance 

We also have a bonus update for Microsoft shops looking to enable real-time data integration with legacy databases via change data capture (CDC). Available now in Redpanda Connect:

• Microsoft SQL Server CDC input for turning your legacy monolith into a streaming microservice

It all stems from Redpanda’s promise of a simple, efficient, interoperable, and safe streaming platform that's built for the agentic AI era. Let’s take a sneak peek at the highlights.

Shadowing: Enterprise disaster recovery that's simple

In today’s cloud landscape, where a downed system can have a massive impact on revenue and customer trust, high availability is table stakes. The real game is resilience and business continuity. It’s the answer to the question your CISO and your board are asking: what happens when the entire cloud region goes dark?

However, there's a problem: Disaster recovery in the Apache Kafka^® ecosystem has always been a painful, laborious process involving clunky tools. Not anymore.

Meet Shadowing, our new business continuity feature that provides a complete, byte-for-byte, offset-preserving replica of your entire production cluster in a different region. Shadowing creates a fully functional, hot-standby clone of your entire Redpanda cluster — topics, configs, consumer group offsets, ACLs, schemas — the works! 

When disaster strikes, you’re not restoring from a day-old backup. You’re failing over to a clone that’s seconds behind production. We’re talking Recovery Point Objectives (RPOs) measured in a few seconds and similar Recovery Time Objectives (RTOs), limited only by timeout settings for producers and consumers. In business terms, you lose a few heartbeats of data and you’re back online before your customers even notice.

The only thing faster than recovering from a disaster with a shadow cluster is setting it up in the first place. Any cluster can create a shadow link to a source cluster. With a few lines of configuration or using the interactive process in Redpanda Console, you can enable a shadow link in seconds to start replicating your most critical workflows.

Shadowing is built into the Redpanda broker itself and uses the standard Kafka API to link clusters. No MirrorMaker 2 or Redpanda Migrator connectors are used under the hood. Shadowing combines an asynchronous replication mechanism with offset preservation, allowing for multi-region disaster recovery with simpler client failover procedures. It’s designed for workloads with high-throughput, low-latency requirements and can operate with a low, but nonzero, RPO and RTO.

Learn more about Redpanda Shadowing in the docs →

Cloud Topics: Finally, a home for your "write-once, read-later" data

We all have this type of data — you know the kind: compliance logs, debug streams, raw events for that AI project you’ll start someday. It’s important, but does it really need instantaneous replication across AZ boundaries, or to live on the same screaming-fast, high-performance SSDs as your mission-critical event data? No. Some data sets are latency‑critical (e.g., payments, trading, cybersecurity), and others are latency‑tolerant (e.g., observability, model training, compliance reporting). Treating those workloads the same is inefficient.

Cloud Topics fixes this by allowing you to define and align operational costs to business value per topic — within the same Redpanda cluster. With Cloud Topics, each batch of messages is passed straight through and written to cost‑effective object storage (S3/ADLS/GCS) while topic metadata is managed in-broker — replicated via Raft for high availability — so the cluster can do its job (partition leadership, replica placement, quotas, governance). 

This approach virtually eliminates the cross-AZ network traffic associated with data replication. You keep millisecond performance where it matters, and pay object‑store prices for replication where it doesn’t, without sacrificing durability. This flexibility allows you to add high-throughput workloads that previously weren’t economically viable to the same environment that runs your critical low-latency workloads. Contrast this with Confluent, where you may need a mix of Kora-powered Confluent Cloud clusters (standard/dedicated or Freight) and the separate Confluent WarpStream engine (BYOC) to satisfy different requirements.

Here's the business impact:

• Dramatically lower TCO: Sidestep steep cloud provider networking charges for compliance, security, training data, or batch analytics.
  
  
• Architectural simplification: Stop using a separate platform or cluster just to handle latency-tolerant streaming workloads. Learn, manage, scale, observe, and secure one system for all streams, even as workload requirements shift. This means one Devex, UI, RBAC model, and GitOps workflow to rule them all.
  
  
• A single multimodal streaming engine: Run traditional Redpanda topics for low latency and data safety, use write caching for ultra-low latency, Iceberg Topics for push-button lakehouse ingestion, and Cloud Topics for cost-efficient, high-throughput streaming — all in one platform. That’s less infrastructure to manage and a cleaner mental model for every team.

Cloud Topics is a beta feature for v25.3. Contact us to enable it →

Iceberg Topics + Google BigQuery: Stream-to-table catalog support reaches the shores of BigLake

If you’re on GCP, your lakehouse life runs through BigLake/Dataplex and BigQuery. With 25.3, Redpanda’s native Iceberg integration can automatically register streaming tables to the Google BigLake metastore, so those tables are discoverable, secure, and governed alongside the rest of your GCP analytics estate.

This means fewer governance exceptions, faster analytics onboarding, and a broader view of data assets, leading to better insights. Your data science team using Apache Spark™, your BI analysts in BigQuery, and your ML platform can all query the exact same, single copy of the data the second it arrives. This democratizes access to real-time event streams, eliminates data duplication, slashes storage costs, and reduces your time-to-insight from hours or days to seconds.

Google BigLake metastore support complements existing REST catalog support for Redpanda Iceberg Topics with Databricks Unity Catalog, Snowflake Open Catalog, and AWS Glue.

Read more about BigLake metastore support here →

Redpanda Connect: new MSSQL CDC input (because the business still runs on SQL Server)

Every established enterprise has a crown jewel. That critical, battle-hardened OLTP database that runs a huge part of the business and that everyone is terrified to touch. The data inside is priceless, but it’s locked away, inaccessible to your modern, event-driven applications.

Our new Microsoft SQL Server CDC input component for Redpanda Connect is the key to safely unlocking that value. Using dedicated change tables, the connector non-invasively captures every single insert, update, and delete from your SQL Server tables in real time and streams them into Redpanda with minimal impact on the source database’s performance.

SQL Server CDC performance

In our environment, Redpanda Connect synced the same SQL Server table at a notably higher ingest rate than an alternative hosted Kafka + CDC service under similar conditions*. The new Microsoft SQL Server CDC input for Redpanda Connect sustained ~40 MB/sec average and completed the initial snapshot in about 3 minutes (3:15). The alternative ran at ~14.5 MB/sec and took about 8 minutes (8:04).

*Methods: One table (5 million rows); SQL Server co-located with Azure instance running Redpanda Connect (instance specs: 4 vCPUs bound to 1 logical core, 16 GB memory); default settings used; identical schema/workload across runs. Your results will vary by table size, change rate, and environment.

This is your playbook for low-risk modernization. Instead of a high-risk, “big bang” migration, you can pursue an evolutionary strategy. Leave the legacy system running, stream its data into Redpanda, and start building new microservices and real-time analytics around it. This reduces risks to build new event-driven architectures and allows you to unify your company’s entire data story — from decades-old transactions to real-time microservice events — on a single, powerful streaming data plane.

The Microsoft SQL Server CDC connector is an enterprise connector and is available starting with Redpanda Connect version 4.67.5. It is also available now on Redpanda Cloud. Learn more in the Redpanda Connect docs →

Ready to upgrade?

Redpanda is the data streaming platform for the agentic AI era — simple to run, efficient at scale, interoperable with your current stack, and safe for the enterprise with security and governance built in. In keeping with this mission, Redpanda 25.3 is all about providing the uncompromising resilience, game-changing infrastructure efficiency, and open interoperability that modern enterprises demand for their streaming workloads. 

Let's recap the good stuff:

• Shadowing: Create a shadow link, monitor lag and throughput on your shadow cluster, and run a DR drill. It’s engineered for seamless active‑passive recovery with offset fidelity so failover behaves the way clients expect.
  
  
• Cloud Topics: Expand the aperture of event streaming to fine-grained observability, analytics and cybersecurity use cases with maximum resilience against cloud AZ failures, without the sticker shock of cloud networking costs.
  
  
• Iceberg Topics + GCP BigLake: Land streaming events into Iceberg tables for BigQuery users and let BigLake’s governance tooling do the rest — same catalog, same policies, no IAM headaches.
  
  
• SQL Server CDC for Redpanda Connect: Connect the system that runs the business to the platform that runs your events, then route them anywhere with our connector ecosystem.

Dive into what’s new and get started today with an Enterprise Edition trial, or spin up instantly with Redpanda Serverless!