Redpanda Cloud - Annual Commits (BYOC & Dedicated/Serverless)

What do you like best about the product?

Transitioning our event streaming pipelines to the Redpanda Data Platform has substantially reduced our operational overhead while maintaining robust throughput. The primary advantage is its single binary C++ architecture, which completely eliminates the need for JVM garbage collection tuning and ZooKeeper dependencies, delivering predictable, ultra low p99 latencies under heavy load. Because Redpanda is natively compatible with the Apache Kafka API, we were able to migrate our existing producers, consumers, and connectors without making any code changes to our application layer. Features like built in Tiered Storage which automatically offloads historical log segments to object storage have significantly lowered our local storage costs, while the integrated console makes monitoring topic throughput and consumer lag straightforward right out of the box...

What do you dislike about the product?

The main limitations stem from documentation depth for niche setups and a heavy reliance on command line management for complex tasks. While the built in web dashboard works well for high level monitoring, detailed administrative actions still depend entirely on the rpk CLI tool. Additionally, while the core product documentation is thorough, finding specific guidance for complex deployment edge cases occasionally requires reaching out to their community Slack rather than finding immediate answers in the official docs, and certain legacy Kafka Connect plugins require extra validation before deploying at scale!...

What problems is the product solving and how is that benefiting you?

We needed a high-throughput event streaming platform that wouldn't require excessive engineering overhead to maintain. Redpanda solved our infrastructure cost and operational efficiency challenges by using a thread-per-core architecture that delivers higher throughput on fewer, smaller compute nodes compared to traditional options. By eliminating complex JVM tuning and external quorum management, our engineering team spends significantly less time managing cluster infrastructure and can onboard new developers to our data streaming platform much faster...

What do you like best about the product?

Easy to use for processing large amounts of data. Works fast and easy.

What do you dislike about the product?

It's not for everyone, you need some technical skills to use it.

What problems is the product solving and how is that benefiting you?

It helps handle data more efficiently and makes it a lot faster.

What do you like best about the product?

RPK is great and easy to integrate into existing tools. They’re constantly improving the UI/UX, which makes the overall experience smoother. The AI agent is usually spot-on, and when I do need help, opening tickets and getting solutions is super fast and efficient. The kafka connect and red panda connect options are a great way to bring existing data into the streaming pipe. Support and account managers are great, they're the one vendor we're always happy to talk to.

What do you dislike about the product?

Compared to the alternatives, I see very few downsides. Any issues or potential drawbacks tend to get addressed quickly through UI updates, rpk updates, and similar improvements.

What problems is the product solving and how is that benefiting you?

Real-time data translates into better operations across all our orgs. Our platform relies on high-volume data streaming, and Redpanda solves one of our most critical needs: delivering real-time data for both the platform and the business.

What do you like best about the product?

- Lower resources requirements than of the kafka cluster of the same capacity
- Tier storage support. Offloading local data to S3/GCS is very handy as allows to not pay for the huge local disks in order to maintain longer data retention periods
- Very capable as a streaming application - we run it slightly above the recommended tier limit (on the production side) and the clusters can handle it with no sweat
- Quick and responsive support, including cases that require deep tech investigations. It helps a lot that the maintainer of franz-go (best kafka client for golang works for Redpanda)
- The app itself is lightweight and works well for the integration testing using test containers
- Support of google as auth provider for user management, allows to avoid 3rd party accounts on top of ones already existing in the organization

What do you dislike about the product?

From a technical perspective - nothing. It works well and we're glad

What problems is the product solving and how is that benefiting you?

Straight queue-like data streaming. We're pushing (and consuming) 1.1 GB per second with 4 days retention through a Redpanda cluster and the cluster works in a manner that we don't think about it and we don't need to maintain it. We just know that it's up-to-date and maintained.

What do you like best about the product?

It’s easy to use, low-maintenance, and the throughput is good.

What do you dislike about the product?

Integrations with other DBs, like ClickHouse, aren’t great. Also, the managed pipelines they provide aren’t very customizable.

What problems is the product solving and how is that benefiting you?

Infrastructure maintenance for deployments, including managing the infrastructure.

What do you like best about the product?

Nice user console/dashboard to track metrics and usage. Very easy to integrate across different programming languages. Easy integration with other vendors like Clickhouse. Never had any issues with performance. Great customer service.

What do you dislike about the product?

Some of the errors can be cryptic sometimes but I guess that's the nature of Kafka.

What problems is the product solving and how is that benefiting you?

We use for a trading and risk system to stream all sorts of market data. It's been extremely fast and had no issues scaling to consume large amounts of data.

What do you like best about the product?

Highly performant and reliable software for a Kafka implementation

What do you dislike about the product?

Company is recently diverting a lot of resources working on features not useful for us rather than improving the core functionality.

What problems is the product solving and how is that benefiting you?

It’s delivering a more performant Kafka implementation than Apache Kafka

What do you like best about the product?

The biggest win has been operational: Redpanda is a single binary with no JVM and no ZooKeeper/KRaft quorum to manage separately. Our previous Kafka cluster needed brokers plus ZooKeeper nodes.

Integrations: Kafka API compatibility was the deciding factor.

UI/UX: Redpanda Console gets used daily to check consumer lag, inspect messages on a topic, and confirm schema registry entries without dropping to rpk. Being able to hand a non-engineer a URL to see whether events are flowing has cut a real amount of Slack back-and-forth.

Performance: p99 produce latency sits sustained. Predictability matters more to us than peak throughput.

Pricing / ROI: Fewer, smaller nodes for the same workload dropped our streaming infra spend.

Support / Onboarding: Always respond fast, shared a Slack channel with high quality of the migration help.

AI/Intelligence: Haven't used too much but will definitely try something out.

What do you dislike about the product?

Observability: Metrics are Prometheus-native and thorough, but mapping them onto the Kafka dashboards and alerts we already had took real effort , names and semantics don't line up one-to-one.

What problems is the product solving and how is that benefiting you?

We use Redpanda as the ingest and fan-out backbone for high-volume telemetry from fleet devices.

The problem it solved was operational cost per unit of throughput. On self-managed Kafka we were carrying 12 brokers plus a coordination quorum, and a meaningful share of my team's time went to broker tuning, GC pauses, and capacity headroom we kept purely to absorb spikes. That was engineering time spent on the transport layer rather than on the product sitting on top of it.

Since moving to Redpanda we run 12 nodes for the same volume, latency is predictable enough, and cluster maintenance has gone from a recurring task to something I mostly don't think about.

What do you like best about the product?

What I like best about Redpanda Streaming is how easy it is to deploy and manage, especially with the BYOC option. The onboarding experience is straightforward, the documentation is clear and practical, and the Terraform support makes it easy to automate deployments and manage the infrastructure as code.

It also integrates well with our existing monitoring solution, which made adoption much easier and allows us to keep using the observability tools and processes we already have in place.

The support experience has also been excellent. Having direct access to the team through Slack is very helpful, and responses are consistently quick and useful when we have questions or need assistance.

Overall, Redpanda significantly reduces the operational overhead of running a streaming platform while still giving us the control and flexibility we need in our own cloud environment.

What do you dislike about the product?

I don’t have any major complaints so far. One area that could become more important for us as we grow is having more self-service options for modifying existing clusters.

For example, being able to scale cluster size up or down, make certain networking changes, or adjust other infrastructure settings directly would be useful. To my knowledge, some of these changes currently require opening a support ticket rather than being handled through self-service.

The support team is responsive, so this hasn’t been a significant issue for us, but having more of these capabilities available directly would make managing the platform even easier as our usage scales.

What problems is the product solving and how is that benefiting you?

Redpanda Streaming helps us offload the operational burden of managing a business-critical streaming infrastructure.

Previously, this was an area that could create reliability and operational issues because it required specialized expertise and ongoing attention that was not a core focus for our team. With Redpanda, we can rely on a managed platform while still maintaining the level of control we need.

The main business benefit is that our engineering team can spend less time operating and troubleshooting streaming infrastructure and more time focusing on our core product. It also reduces the operational risk around a critical part of our architecture and gives us more confidence as we scale.

What do you like best about the product?

I like Redpanda Streaming for its reliable fast streaming capabilities with large volumes. It provides strong performance and reliable event streaming capabilities, which is important for our real-time data processes. The initial setup was relatively straightforward for basic use cases.

What do you dislike about the product?

I find that Redpanda Streaming delivers strong performance and reliability, but I believe improvements in documentation, advanced integrations, monitoring capabilities, and ease of administration would help create a smoother user experience, especially for complex deployments. The platform requires a learning curve for new users, and advanced deployment, monitoring, and optimization may need additional expertise. Some integrations and tooling options could also be expanded further.

What problems is the product solving and how is that benefiting you?

I use Redpanda Streaming to manage real-time data pipelines, ensuring efficient processing and reliable delivery. It reduces data delays, supports scalable communication, and improves the performance of data-driven workflows across applications.