Tools that treat your data like the main event.
Finnstream builds deep, data-centric software — from a Kafka desktop workspace that testers actually love, to an open-source streaming database that removes partitions entirely.
Four tools, one philosophy
Every Finnstream product starts from the same idea: answer “what’s in my data and what is it doing” — not “what is my infrastructure doing”.
Stream, replay, tag, filter, inspect, reconstruct, test and manage Kafka data in one desktop app — with a microservice-deployed Multi-User Web Edition on its way so teams can share connections, test-data samples, SL filters and Live Views.
Explore Kafka Streamyard Open Source · In Testing
A clean-sheet streaming platform and distributed database in Rust. Operational today and undergoing extensive testing over the next few months — with official .NET, Go, Java, Node.js, Python and Rust SDKs on GitHub.
Explore Whitewater & SDKs Coming Soon
Coming soon — built from Kafka Streamyard to help manage Whitewater Riverbeds. Browse Domains and Feeds, tail records, replay samples, run playbooks and design pipelines with the visual Whitewater Stream Builder.
Preview Whitewater UI Mac App Store Soon
Almost ready for the Mac App Store. Combines a 73-command customizable action deck, expandable Explorer file tree, 2-Pane & 4-Pane split views, AI-tested Boolean filters, Named File Baskets, Image Studio and a multi-tab Zsh terminal.
Explore FileYardFeatures aren’t a checkbox — they’re the workflow
Most tools stop at “browse and inspect”. Finnstream tools carry the job through to the end: find it, filter it, replay it, automate it, export the evidence.
Data-centric, not infra-centric
Other tools show you brokers, partitions and offsets. Finnstream tools show you the data — the messages, files and records — then give you everything needed to act on it, in the same window.
End-to-end, not browse-only
A topic browser lets you look. Kafka Streamyard and Whitewater UI let you look and then: build a filter, turn it into a sample, replay it into a test, script it in a playbook, and export the result as evidence.
Built by daily users
These tools were written by engineers debugging real streaming systems. The depth — persisted investigations, session variables, partition calculators, copy tasks — comes from needing it, not from a feature matrix.
Investigate the whole flow, not one topic at a time
Kafka Streamyard’s Live Views merge up to 30 topics into one chronological timeline — the workflow as it actually happened — with per-topic filters and an activity-aware flow chart.
- Live and historical multi-topic playback
- JSON & XML filtering with autocomplete and AI assist
- Persisted investigation state across restarts
A quick taste of the difference
Whitewater removes what other platforms make you manage. The full comparisons put every Finnstream tool next to the alternatives.
| Capability | WhitewaterFinnstream · open source | Apache Kafkathe incumbent |
|---|---|---|
| Public resource modelwhat applications must learn | Feeds, keys, cursors — no partitions | Topics, partitions, offsets, consumer groups |
| Durability baseline | RF3 quorum in the protocol, no tuning | Configurable — easy to get wrong |
| Current-state queries | Replicated Indexes & StateStores built in | Requires external DB or Streams app |
| Scaling a stream | Add nodes — ranges move internally | Repartition + rebalance planning |
Whitewater is operational — and open on GitHub
The core Rust platform and all six official SDKs (.NET, Go, Java, Node.js, Python, Rust) are operational today and undergoing extensive testing over the next few months. Whitewater UI (coming soon, built from Kafka Streamyard) will add visual Riverbed management and a Whitewater Stream Builder.
Work with your data, not around your tools.
Pick the tool that matches your platform — or start with the open-source engine and grow into the rest.