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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

Amazon Managed Streaming for Apache Kafka (Amazon MSK) simplifies the process of creating and operating applications that leverage Apache Kafka for handling streaming data. As an open-source framework, Apache Kafka enables the construction of real-time data pipelines and applications. Utilizing Amazon MSK allows you to harness the native APIs of Apache Kafka for various tasks, such as populating data lakes, facilitating data exchange between databases, and fueling machine learning and analytical solutions. However, managing Apache Kafka clusters independently can be quite complex, requiring tasks like server provisioning, manual configuration, and handling server failures. Additionally, you must orchestrate updates and patches, design the cluster to ensure high availability, secure and durably store data, establish monitoring systems, and strategically plan for scaling to accommodate fluctuating workloads. By utilizing Amazon MSK, you can alleviate many of these burdens and focus more on developing your applications rather than managing the underlying infrastructure.

Description

IBM Event Streams is a comprehensive event streaming service based on Apache Kafka, aimed at assisting businesses in managing and reacting to real-time data flows. It offers features such as machine learning integration, high availability, and secure deployment in the cloud, empowering organizations to develop smart applications that respond to events in real time. The platform is designed to accommodate multi-cloud infrastructures, disaster recovery options, and geo-replication, making it particularly suitable for critical operational tasks. By facilitating the construction and scaling of real-time, event-driven solutions, IBM Event Streams ensures that data is processed with speed and efficiency, ultimately enhancing business agility and responsiveness. As a result, organizations can harness the power of real-time data to drive innovation and improve decision-making processes.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Apache Kafka Yes 
Waterstream Yes 
5X Yes 
Amazon Data Firehose Yes 
Amazon EC2 Yes 
Argonaut Yes 
Datadog Yes 
IBM MQ on Cloud No 
Lenses Yes 
New Relic Yes 
Onehouse Yes 
Protegrity Yes 
Sumo Logic Yes 
Tenzir Yes 
kPow Yes 
meshIQ No 

Integrations

Apache Kafka Yes 
Waterstream Yes 
5X No 
Amazon Data Firehose No 
Amazon EC2 No 
Argonaut No 
Datadog No 
IBM MQ on Cloud Yes 
Lenses No 
New Relic No 
Onehouse No 
Protegrity No 
Sumo Logic No 
Tenzir No 
kPow No 
meshIQ Yes 

Pricing Details

$0.0543 per hour
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/msk/

Vendor Details

Company Name

IBM

Founded

1911

Country

United States

Website

www.ibm.com/products/event-streams

Product Features

Streaming Analytics

Data Enrichment No 
Data Wrangling / Data Prep No 
Multiple Data Source Support No 
Process Automation No 
Real-time Analysis / Reporting No 
Visualization Dashboards No 

Product Features

Message Queue

Asynchronous Communications Protocol No 
Data Error Reduction No 
Message Encryption No 
On-Premise Installation No 
Roles / Permissions No 
Storage / Retrieval / Deletion No 
System Decoupling No 

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