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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

Data processing that integrates both streaming and batch operations while being serverless, efficient, and budget-friendly. It offers a fully managed service for data processing, ensuring seamless automation in the provisioning and administration of resources. With horizontal autoscaling capabilities, worker resources can be adjusted dynamically to enhance overall resource efficiency. The innovation is driven by the open-source community, particularly through the Apache Beam SDK. This platform guarantees reliable and consistent processing with exactly-once semantics. Dataflow accelerates the development of streaming data pipelines, significantly reducing data latency in the process. By adopting a serverless model, teams can devote their efforts to programming rather than the complexities of managing server clusters, effectively eliminating the operational burdens typically associated with data engineering tasks. Additionally, Dataflow’s automated resource management not only minimizes latency but also optimizes utilization, ensuring that teams can operate with maximum efficiency. Furthermore, this approach promotes a collaborative environment where developers can focus on building robust applications without the distraction of underlying infrastructure concerns.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

New Relic Yes 
Protegrity Yes 
5X Yes 
Amazon EC2 Yes 
Apache Kafka Yes 
Argonaut Yes 
CData Connect No 
DataBuck No 
Google Cloud Bigtable No 
Google Cloud Confidential VMs No 
Google Cloud Datastream No 
Google Cloud IoT Core No 
Google Cloud Managed Service for Apache Airflow No 
Google Cloud Platform No 
Google Cloud Profiler No 
Lenses Yes 
Sedai No 
Sumo Logic Yes 
Telmai No 
Tenzir Yes 

Integrations

New Relic Yes 
Protegrity Yes 
5X No 
Amazon EC2 No 
Apache Kafka No 
Argonaut No 
CData Connect Yes 
DataBuck Yes 
Google Cloud Bigtable Yes 
Google Cloud Confidential VMs Yes 
Google Cloud Datastream Yes 
Google Cloud IoT Core Yes 
Google Cloud Managed Service for Apache Airflow Yes 
Google Cloud Platform Yes 
Google Cloud Profiler Yes 
Lenses No 
Sedai Yes 
Sumo Logic No 
Telmai Yes 
Tenzir No 

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 No 

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

Google

Founded

1998

Country

United States

Website

cloud.google.com/dataflow

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

Streaming Analytics

Data Enrichment Yes 
Data Wrangling / Data Prep Yes 
Multiple Data Source Support Yes 
Process Automation Yes 
Real-time Analysis / Reporting Yes 
Visualization Dashboards Yes 

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