Skip to content
SPECIFICTION
Get listed

Confluent Cloud vs StreamHouse

Confluent Cloud

confluent.io

StreamHouse

streamhouse.app

Side by side

FigureConfluent CloudStreamHouse
Price from$385/mo—
Free planYes—
Free trialYes—
Open source——
WebYesYes
LinuxYes—
APIYesYes
Self-hosted—Yes
Plans published40
Spec score · Event Streaming Platforms8.4 (#4)6.7 (#19)

Plans

Confluent Cloud

  • BasicFree
  • Standard$385 a month
  • Enterprise$895 a month
  • Confluent CloudFree

Confluent Cloud pricing →

StreamHouse

No plans published.

StreamHouse pricing →

In their own words

Confluent Cloud

Confluent Cloud is a managed data streaming platform built on a serverless Apache Kafka engine. It is designed for real-time streaming, event-driven applications, analytics, and AI/ML workloads. Cluster choices include Basic, Standard, Enterprise, and Freight, as well as Dedicated clusters with pre-provisioned resources. Confluent says its cloud-native engine adjusts cluster infrastructure to workload needs. Cluster Linking replicates, synchronizes, and shares data across regions, public clouds, and organizations. The service includes managed Kafka connectors for databases, data lakes, and warehouses, serverless processing with Apache Flink, and a managed Stream Governance suite. Tableflow can materialize Kafka topics and schemas as Apache Iceberg and Delta Lake tables. Listed security features include RBAC, self-managed encryption keys, client-side field-level encryption, and audit logs. Users can manage clusters and topics through a web UI or CLI; supported client languages include Java, Python, .NET, Go, Node.js, and C/C++. It is available on AWS, Azure, and Google Cloud across more than 100 regions. A free plan is available; paid plans start at $385/mo, and new signups receive a 30-day trial.

Visit confluent.io

StreamHouse

StreamHouse is an open-source, self-hostable system combining event streaming, processing, schema management, and observability. Developers can ingest events through REST, gRPC, or the Kafka protocol, then use its SQL engine to query streams and transform events in pipelines. Pipelines can continuously send SQL-transformed results to PostgreSQL and be managed through the CLI or an SDK. StreamHouse stores data in S3 and describes that storage as S3-native. Its schema registry supports JSON Schema, Avro, and Protobuf with compatibility checking. Listed sinks include PostgreSQL, S3, and Elasticsearch. Monitoring includes Prometheus metrics, Grafana dashboards, and real-time WebSocket metrics. Organization-scoped isolation and permissioned API keys provide access controls. Python and TypeScript SDKs are documented, while CLI installation is available through Homebrew or a shell installer. The project uses Apache License 2.0, and its stateless agents can scale like web servers.

Visit streamhouse.app