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Amazon Kinesis VS Azure Event Hubs

Compare Amazon Kinesis VS Azure Event Hubs and see what are their differences

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Amazon Kinesis logo Amazon Kinesis

Amazon Kinesis services make it easy to work with real-time streaming data in the AWS cloud.

Azure Event Hubs logo Azure Event Hubs

Learn about Azure Event Hubs, a managed service that can ingest and process massive data streams from websites, apps, or devices.
  • Amazon Kinesis Landing page
    Landing page //
    2022-01-28
  • Azure Event Hubs Landing page
    Landing page //
    2023-03-27

Amazon Kinesis features and specs

  • Real-time data processing
    Amazon Kinesis allows for real-time processing of data streams, enabling rapid ingestion and analysis of data as it arrives.
  • Scalability
    Kinesis is highly scalable and can handle massive volumes of streaming data, expanding automatically to meet your needs.
  • Fully managed service
    As a fully managed service, Kinesis handles infrastructure maintenance, provisioning, and scaling, reducing operational overhead.
  • Integration with AWS ecosystem
    Kinesis integrates seamlessly with other AWS services such as Lambda, Redshift, S3, and Elasticsearch, facilitating comprehensive data workflows.
  • Multiple data stream applications
    The service supports different types of data stream applications including data delivery, analytics, and real-time processing, making it versatile.
  • Security
    Offers robust security through integration with AWS Identity and Access Management (IAM), encryption at rest with AWS Key Management Service (KMS), and in-transit encryption.

Possible disadvantages of Amazon Kinesis

  • Cost
    While pricing is scalable, costs can escalate quickly with high data throughput and storage requirements, potentially becoming expensive for large-scale implementations.
  • Complex setup and management
    Despite being a managed service, the initial setup and tuning of Kinesis can be complex and may require specialized knowledge.
  • Latency
    Although designed for real-time data processing, there can be minor latency involved that might not fit ultra-low latency requirements.
  • Limited data retention
    Kinesis typically supports up to 7 days of data retention in streams, which might be insufficient for use cases requiring longer retention periods without extra storage solutions.
  • API Rate Limits
    API access to Kinesis is subject to rate limits, which could impact applications requiring high-frequency data ingestion and retrieval.
  • Dependence on AWS services
    Tight integration with AWS services can pose a challenge for organizations looking for a multi-cloud or cloud-agnostic strategy.

Azure Event Hubs features and specs

  • Scalability
    Azure Event Hubs can handle millions of events per second, making it highly scalable for large-scale data ingestion solutions.
  • Fully Managed
    As a fully managed service, it reduces the overhead associated with managing infrastructure, allowing teams to focus on application development.
  • Integration
    Seamlessly integrates with other Azure services like Azure Stream Analytics, Azure Functions, and more, making it a versatile solution within the Azure ecosystem.
  • Data Retention
    Supports event retention of up to seven days, allowing applications to replay streams and facilitating debugging or application state recovery.
  • Security
    Offers comprehensive security features, including encryption at rest and in transit, VNet service endpoints, and Shared Access Signatures (SAS) for access control.

Possible disadvantages of Azure Event Hubs

  • Complexity in Setup
    The initial setup and configuration can be complex for new users, especially those unfamiliar with Azure services.
  • Cost
    Costs can accumulate quickly, particularly with high-throughput or extensive data retention requirements, potentially impacting budget-conscious projects.
  • Limited On-premises Integration
    Primarily designed for cloud environments, making it less suitable for on-premises scenarios without additional integration layers.
  • Latency
    Although generally low, latency can become noticeable in high-load scenarios, which might affect applications requiring real-time processing.
  • Partition Management
    Dynamic partition scaling is not available. Once set, partition counts cannot be changed without creating a new event hub, which requires thoughtful upfront planning.

Analysis of Amazon Kinesis

Overall verdict

  • Yes, Amazon Kinesis is a good option for organizations that need to process and analyze large streams of data in real-time. Its scalability, ease of integration with existing AWS infrastructure, and advanced features make it a preferred choice for many enterprise-level applications.

Why this product is good

  • Amazon Kinesis is generally considered a robust choice for real-time data processing because it can ingest, buffer, and process streaming data at scale. It offers features like durable storage, the ability to handle high throughput with low latency, and seamless integration with other AWS services. This makes it particularly well-suited for applications that require real-time analytics, data lake integrations, or reacting to changing data streams with minimal delay.

Recommended for

  • Organizations dealing with large quantities of streaming data
  • Businesses needing real-time data analytics and processing
  • Developers looking for seamless integration with AWS services
  • Teams wanting to build real-time machine learning models
  • Companies implementing IoT solutions requiring data streaming

Amazon Kinesis videos

+ Add

AWS Big Data - Amazon Kinesis Analytics Introduction and Demonstration

More videos:

  • Review - Analyzing Data Streams in Real Time with Amazon Kinesis: PNNL's Serverless Data Lake Ingestion

Azure Event Hubs videos

+ Add

Messaging with Azure Event Hubs

Category Popularity

0-100% (relative to Amazon Kinesis and Azure Event Hubs)

Amazon Kinesis

Azure Event Hubs

Stream Processing
79 79%
Stream Processing
21% 21
Data Management
77 77%
Data Management
23% 23
Big Data
77 77%
Big Data
23% 23
Data Integration
100 100%
Data Integration
0% 0

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Amazon Kinesis and Azure Event Hubs

Amazon Kinesis Reviews

Top 10 AWS ETL Tools and How to Choose the Best One | Visual Flow
Amazon Kinesis was built to handle massive amounts of data, allowing it to be uploaded to a Redshift cluster. After the event stream is read and the data is transformed, it is placed into a table in Amazon SCTS in an Amazon ES domain. Thus, there is no need to use a server (instead, you need to integrate AWS ETL and AWS Lambda).
Source: visual-flow.com
6 Best Kafka Alternatives: 2022’s Must-know List
Kinesis enables streaming applications to be managed without additional infrastructure management. This highly scalable platform can process data from various sources with low latency. Known for its speed, ease of use, reliability, and capability of cross-platform replication, Amazon Kinesis is one of the most popular Kafka Alternatives. It is used for many purposes,...
Source: hevodata.com
Top 15 Kafka Alternatives Popular In 2021
Amazon Kinesis, also known as Kinesis Streams, is a popular alternative to Kafka, for collecting, processing, and analyzing video and data streams in real-time. It offers timely and insightful information, streaming data in a cost-effective manner with complete flexibility and scalability. It is easy to ingest data encompassing audios, videos, app logs, etc. It offers an...
Source: www.spec-india.com
16 Top Big Data Analytics Tools You Should Know About
Amazon Kinesis is a massively scalable, cloud-based analytics service which is designed for real-time applications.
Source: www.analytixlabs.co.in

Azure Event Hubs Reviews

We have no reviews of Azure Event Hubs yet.
Be the first one to post

Social recommendations and mentions

Based on our record, Amazon Kinesis should be more popular than Azure Event Hubs. It has been mentiond 26 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Amazon Kinesis mentions (26)

  • FINTECH SCALABILITY
    Real-Time Processing — With Amazon Kinesis and Amazon DynamoDB, fintech firms can analyze transactions instantly, identify fraud before it happens. - Source: dev.to / 3 months ago
  • Top 7 Kafka Alternatives For Real-Time Data Processing
    Amazon Kinesis is a fully managed real-time data streaming service by AWS, designed for large-scale data ingestion and processing. - Source: dev.to / 9 months ago
  • AWS Operational issue – Multiple services in us-east-1
    Https://aws.amazon.com/kinesis/ > Amazon Kinesis Data Streams is a serverless streaming data service that simplifies the capture, processing, and storage of data streams at any scale. I'd never heard of that one. - Source: Hacker News / 10 months ago
  • Event-Driven Architecture on AWS
    Event Consumers: Services that actively listen for events and respond accordingly. These consumers can be easily implemented using microservices, AWS Lambda or Amazon Kinesis (for ingesting, processing, and analyzing streaming data in real-time). - Source: dev.to / about 1 year ago
  • AWS DEV OPS Professional Exam short notes
    When you see Amazon Kinesis as an option, this becomes the ideal option to process data in real time. Amazon Kinesis makes it easy to collect, process, and analyze real-time, streaming data so you can get timely insights and react quickly to new information. Amazon Kinesis offers key capabilities to cost effectively process streaming data at any scale, along with the flexibility to choose the tools that best suit... - Source: dev.to / about 1 year ago
View more

Azure Event Hubs mentions (4)

  • Anyone routing firewall logs to Microsoft Event Hubs?
    We're looking into some sort of cloud-based solution to route our Palo Alto firewall logs to across our customer base. I'm with an MSP that manages over a hundred PA firewalls. I was intrigued by the Event Hubs (https://azure.microsoft.com/en-us/products/event-hubs/) solution as a way to push logs to it and then ingest them from there into our SIEM, without having to deal with challenges of multi-tenancy and... Source: over 2 years ago
  • Microsoft Releases Stream Analytics No-Code Editor into General Availability
    Microsoft released Azure Stream Analytics no-code editor, a drag-and-drop canvas for developing jobs for stream processing scenarios such as streaming ETL, ingestion, and materializing data to data into general availability. The no-code editor is hosted in the company’s big-data streaming platform and event ingestion service, Azure Event Hubs. Interestingly, the offering follows up after Confluent's recent release... Source: over 2 years ago
  • Infrastructure as code (IaC) for Java-based apps on Azure
    Sometimes you don’t need an entire Java-based microservice. You can build serverless APIs with the help of Azure Functions. For example, Azure functions have a bunch of built-in connectors like Azure Event Hubs to process event-driven Java code and send the data to Azure Cosmos DB in real-time. FedEx and UBS projects are great examples of real-time, event-driven Java. I also recommend you to go through 👉 Code,... - Source: dev.to / over 2 years ago
  • Setting up demos in Azure - Part 1: ARM templates
    For event infrastructure, we have a bunch of options, like Azure Service Bus, Azure Event Grid and Azure Event Hubs. Like the databases, they aren't mutually exclusive and I could use all, depending on the circumstance, but to keep things simple, I'll pick one and move on. Right now I'm more inclined towards Event Hubs, as it works similarly to Apache Kafka, which is a good fit for the presentation context. - Source: dev.to / about 4 years ago

What are some alternatives?

When comparing Amazon Kinesis and Azure Event Hubs, you can also consider the following products

Confluent - Confluent offers a real-time data platform built around Apache Kafka.

Azure Stream Analytics - Azure Stream Analytics offers real-time stream processing in the cloud.

Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.

PieSync - Seamless two-way sync between your CRM, marketing apps and Google in no time

Spark Streaming - Spark Streaming makes it easy to build scalable and fault-tolerant streaming applications.

Amazon Elasticsearch Service - Amazon Elasticsearch Service is a managed service that makes it easy to deploy, operate, and scale Elasticsearch in the AWS Cloud.

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