Streaming with Apache Kafka

A fully managed Kafka service that allows you to build real-time, distributed data streaming pipelines so you can collect, process, store, and move millions of events per minute in a cost-efficient manner that’s 100% compatible with open source Apache Kafka.

OCI Stream with Apache Kafka (5:46)

Why OCI Streaming with Apache Kafka?

Leverage the high-throughput, low-latency Apache Kafka event streaming platform, fully managed on Oracle Cloud Infrastructure (OCI).

Fully managed

Apache Kafka service

100%

Compatible with Apache Kafka

99.9%

Availability SLA

Cost efficient

Simple and user-friendly pricing with an industry-leading price-performance ratio

Secure

Data encrypted at rest and in transit; integrated with OCI Key Management Service

Open source ecosystem

Out-of-the-box support for all open source tools and connectors built for Apache Kafka

OCI competitive pricing designed for you

Up to 31% less costly than Amazon Managed Streaming for Apache Kafka (Amazon MSK) and up to 73% less costly than Confluent.

Pricing comparison chart, description below
This bar chart compares the monthly costs associated with different cluster sizes—small, medium, and large—across three services: OCI Streaming with Kafka, Amazon Managed Streaming for Apache Kafka (Amazon MSK), and Confluent Cloud. OCI Streaming with Kafka is the most cost-effective solution. It's up to 31% less costly than Amazon MSK and 73% less costly than Confluent.

Note: Average price comparison done for a small, medium, and large 3-broker cluster with 4, 8, and 16 vCPUs using public pricing of Amazon Managed Streaming for Apache Kafka in AWS US East and Confluent dedicated multizone clusters on AWS US East-4 on November 10, 2024 based on 2 VCPUs having comparable performance to 1 OCPU.

OCI Streaming with Apache Kafka use cases

  • Change data capture (CDC)

    Kafka facilitates CDC by efficiently streaming real-time data changes from databases to downstream systems, enabling immediate processing and integration across applications.

  • Metrics and logs ingestion

    Kafka helps combine logs from different servers within a single feed and transform the data into a standardized format for further analysis by downstream applications.

  • Real-time analytics

    Kafka processes and analyzes continuous streams of data for real-time insights, anomaly detection, and predictive analytics.

  • Web/mobile activity data tracking

    Kafka assists in building a user activity tracking pipeline for real-time processing, monitoring, or loading into data warehousing systems for offline processing and reporting.

How OCI Streaming with Apache Kafka works

Typical use cases for OCI Streaming with Apache Kafka involve processing and analyzing real-time streaming data, such as aggregating and analyzing large volumes of log data from multiple sources to gain immediate insights.

This architecture showcases how data flows from ingestion through OCI Streaming with Apache Kafka to final storage and analytics, enabling seamless, real-time data processing and analysis.


How OCI Streaming with Apache Kafka works diagram, description below

A diagram illustrating a typical data flow using OCI Streaming with Kafka. The diagram consists of three main boxes connected by arrows:

  1. The first box on the left, labeled "Data Ingestion," depicts various data sources that feed into the system: notifications, IoT, and logs.
  2. An arrow labeled "Source Kafka Connector" points from the "Data ingestion" box to the second box, "OCI Streaming with Kafka."
  3. The second box, "OCI Streaming with Kafka," covers the benefits of the core Kafka service on OCI, which is ideal for processing and analyzing streaming data in real time, e.g., analyzing log data from various sources for immediate insights. With this fully managed service, every aspect of Kafka cluster administration is automated, including high availability, patches, upgrades, backups, scaling, and compliance. It’s 100% compatible with Kafka, so there’s no need to change any application code. The service is also cost-efficient, with pay-as-go, competitive pricing based on compute and storage usage.
  4. An arrow labeled "Sink Kafka Connector" points from the "OCI Streaming with Kafka" box to the third box, "Data storage and analytics."
  5. The third box, labeled "Data storage and analytics," depicts how processed data is stored in databases, data lakes, or other storage solutions and analyzed using advanced analytics tools.
  6. This diagram visually depicts the flow of data from ingestion, through Kafka processing, to storage and analytics, highlighting the use of Kafka connectors to manage data movement.

Get started with OCI Streaming with Apache Kafka

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