Sold by: StreamNative Cloud
Deployed on AWS
Unlock the power of data messaging, cost-effective and ready for the enterprise, powered by Apache Kafka® & Apache Pulsar™
Overview
StreamNative is a leading provider of real-time streaming data solutions, specializing in Apache Pulsar, an open-source distributed messaging and streaming platform. Founded by core developers of Apache Pulsar, StreamNative offers a comprehensive suite of products and services that help organizations harness the power of data streams for scalable, low-latency data processing. StreamNative Cloud, the company flagship product, provides a fully managed Pulsar service, enabling businesses to deploy, monitor, and scale streaming applications across any cloud environment. With a focus on flexibility, reliability, and seamless integration, StreamNative also supports Kafka compatibility through its Kafka On StreamNative (KSN) offering, allowing enterprises to bridge the gap between Pulsar and Kafka ecosystems. StreamNative platform powers diverse use cases, from real-time analytics and machine learning pipelines to log management and event-driven architectures. Notably, StreamNative integrates with various AWS services to enable seamless data streaming and processing in the cloud. For example, StreamNative connectors facilitate data ingestion into Amazon S3 for scalable storage, while integration with Amazon Kinesis and AWS Lambda supports real-time analytics and event-driven applications. Additionally, StreamNative Lakehouse Storage support integrates out of the box with AWS S3, enabling users to offload data in both Apache Iceberg and Delta Lake formats for real-time analytics, advanced querying, and compatibility with modern data lake architectures. StreamNative also supports UniLink, a powerful tool that leverages AWS S3 to efficiently replicate data between clusters, ensuring high availability and disaster recovery. By offering tools like the S3 Sink Connector, Pulsar Functions, and managed Pulsar clusters on AWS, StreamNative enables developers to build scalable, efficient, and future-proof data applications across industries such as finance, retail, and IoT.
To learn more about StreamNative Cloud, visit: https://streamnative.io/product
Highlights
- Enjoy the low latency, high durability, and long-term data retention provided by Apache Pulsar, along with seamless Kafka compatibility, without the operational overhead, using cost-effective, enterprise-ready clusters.
- Support both messaging and streaming use cases in your architecture. Build event-driven applications and gain value from your data in real time with features like Pulsar Functions. A rich client library ecosystem includes support C/C++, Python Java, GO, JavaScript, Rust, and more
- Confidently implement data streaming with a managed service backed by the original creators of Apache Pulsar. Clusters are always on the latest stable Pulsar version with enterprise-grade SLAs, on-demand bug fixes, and technical support
Details
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Pricing
Pricing is based on the duration and terms of your contract with the vendor, and additional usage. You pay upfront or in installments according to your contract terms with the vendor. This entitles you to a specified quantity of use for the contract duration. Usage-based pricing is in effect for overages or additional usage not covered in the contract. These charges are applied on top of the contract price. If you choose not to renew or replace your contract before the contract end date, access to your entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/12 months |
|---|---|---|
commit | commitment on the usage of StreamNative managed Apache Pulsar service | $30,000.00 |
Dimension | Cost/unit |
|---|---|
Consumption of resources, such as computing, storage, network etc | $0.10 |
Dimensions summary
This listing uses an annual contract with two pricing dimensions. The first bills for consumption of resources like computing, storage, and network. The second is a commitment you make on usage of the managed Apache Pulsar service. You commit to a usage level for the year, then draw down against it as you consume resources. Billing accrues based on actual usage of compute, storage, and network. The commitment dimension sets your prepaid quantity, while the consumption dimension tracks what you use across those resource types.
Top-of-mind questions for buyers
Consumption covers compute, storage, and network usage. Compute and storage are measured as units of 2 vCPU and 8 GB RAM for stateful and stateless components, billed hourly. Throughput-based usage is measured in Elastic Throughput Units, billed by the highest of ingress, egress, or data-entries each hour.
The architecture scales automatically to handle throughput past your baseline, and you pay for the extra resources you actually use. There are no hard cutoffs that drop messages. Consumption beyond your commitment is billed under the resource consumption dimension.
The commitment dimension sets your prepaid usage level for the year. The consumption dimension meters actual compute, storage, and network use, which draws down against your commitment. Usage accrues hourly. Once you pass the committed amount, extra consumption is billed on top.
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For billing or refund questions, please open a ticket at https://support.streamnative.io
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Delivery details
Software as a Service (SaaS)
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
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AI generated from product descriptions
Distributed Messaging and Streaming Platform
Apache Pulsar open-source distributed messaging and streaming platform with support for both messaging and streaming use cases
Multi-Language Client Library Support
Rich client library ecosystem with support for C/C++, Python, Java, GO, JavaScript, Rust, and additional programming languages
Cloud Storage Integration
Integration with AWS S3 for data offloading in Apache Iceberg and Delta Lake formats, S3 Sink Connector, and cross-cluster data replication via UniLink
Serverless Stream Processing
Pulsar Functions for building event-driven applications and real-time data processing capabilities
Kafka Compatibility Layer
Kafka On StreamNative (KSN) offering enabling seamless interoperability between Pulsar and Kafka ecosystems
Stream Processing Engine
Apache Flink serverless service for real-time data filtering, joining, and enrichment without operational overhead
Data Connectors
120+ pre-built source and sink connectors for integration with AWS services including Amazon S3, Amazon Redshift, Amazon RDS, Amazon DynamoDB, and AWS Lambda
Real-Time Analytics
Apache Iceberg table conversion from Kafka topics to enable downstream analytics across AWS services including Glue, Redshift, Athena, EMR, and SageMaker Lakehouse
Service Availability
99.99% uptime SLA coverage for core Kafka operations with enterprise-grade support and faster issue resolution
Cloud-Native Architecture
Fully managed, elastic, and auto-scaling clusters built on Apache Kafka and Confluent's cloud-native Kafka engine, Kora
Kafka API Compatibility
Full Apache Kafka API compatibility enabling seamless integration with existing Kafka-based applications and tools
Managed Connectors
300+ built-in connectors to popular data systems including Snowflake, MongoDB, Amazon S3, SQS, SNS, Kinesis, Lambda, Bedrock, DynamoDB, and CDC for MySQL and PostgreSQL on RDS
Tiered Storage Architecture
Automatic tiered storage that rolls data from brokers to object storage, delivering up to 8-9x savings in long-term data retention costs
Deployment Flexibility
Multiple deployment options including Bring-Your-Own-Cloud (BYOC), Dedicated, and Serverless cloud products with uptime SLA of 99.99% (Dedicated) and 99.9% (Serverless)
Automated Cluster Management
Fully managed cluster operations including automatic balancing, zero-downtime upgrades, patching, monitoring, and schema registry
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