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Amazon Kinesis VS Spring Cloud Data Flow

Compare Amazon Kinesis VS Spring Cloud Data Flow 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.

Spring Cloud Data Flow logo Spring Cloud Data Flow

Spring Cloud Data Flow is a platform capable of stream and batch data pipelines having the tools to create delicate topologies.
  • Amazon Kinesis Landing page
    Landing page //
    2022-01-28
  • Spring Cloud Data Flow Landing page
    Landing page //
    2023-07-30

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.

Spring Cloud Data Flow features and specs

No features have been listed yet.

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

Spring Cloud Data Flow videos

+ Add

Orchestrate All the Things! with Spring Cloud Data Flow - Eric Bottard & Ilayaperumal Gopinathan

More videos:

  • Review - Demo: Partitioning Batch jobs with Spring Cloud Data Flow & Task
  • Demo - 3 min demo: Spring Cloud Data Flow Metrics

Category Popularity

0-100% (relative to Amazon Kinesis and Spring Cloud Data Flow)

Amazon Kinesis

Spring Cloud Data Flow

Stream Processing
89 89%
Stream Processing
11% 11
Big Data
77 77%
Big Data
23% 23
Data Management
85 85%
Data Management
15% 15
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 Spring Cloud Data Flow

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

Spring Cloud Data Flow Reviews

We have no reviews of Spring Cloud Data Flow yet.
Be the first one to post

Social recommendations and mentions

Based on our record, Amazon Kinesis seems to be a lot more popular than Spring Cloud Data Flow. While we know about 26 links to Amazon Kinesis, we've tracked only 1 mention of Spring Cloud Data Flow. 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 / about 2 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 / 8 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 / 9 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

Spring Cloud Data Flow mentions (1)

  • Dataflow, a self-hosted Observable Notebook Editor
    And a Cloudera project: https://www.cloudera.com/products/cdf.html And an Azure feature: https://docs.microsoft.com/en-us/azure/data-factory/control-flow-execute-data-flow-activity And a Spring feature: https://spring.io/projects/spring-cloud-dataflow. - Source: Hacker News / almost 4 years ago

What are some alternatives?

When comparing Amazon Kinesis and Spring Cloud Data Flow, you can also consider the following products

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

Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.

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

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

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

Lenses - Discover our high quality range of over 40 interchangeable camera lenses including A-mount and E-mount lenses crafted for a range of shooting situations.

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