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Amazon Kinesis VS Oracle DataRaker

Compare Amazon Kinesis VS Oracle DataRaker 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.

Oracle DataRaker logo Oracle DataRaker

Oracle DataRaker unlocks smart meter data and transforms it into compelling, quantifiable, and actionable results with low upfront investment and risk.
  • Amazon Kinesis Landing page
    Landing page //
    2022-01-28
  • Oracle DataRaker Landing page
    Landing page //
    2023-02-09

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.

Oracle DataRaker features and specs

  • Scalability
    Oracle DataRaker is a highly scalable platform that can handle large volumes of data, making it suitable for utilities with extensive customer bases.
  • Advanced Analytics
    It offers advanced analytics capabilities that help utilities gain deeper insights into their operations, enabling data-driven decision-making.
  • Integration
    DataRaker seamlessly integrates with other Oracle utilities applications and third-party systems, ensuring streamlined data flow and enhanced functionality.
  • Cloud-Based
    Being cloud-based, it reduces the need for on-premises infrastructure and simplifies maintenance and updates.
  • Real-Time Monitoring
    Provides real-time monitoring and analytics, allowing utilities to quickly identify and respond to issues.

Possible disadvantages of Oracle DataRaker

  • Cost
    Oracle DataRaker can be expensive, which might be a barrier for smaller utilities or those with limited budgets.
  • Complexity
    The platform can be complex to implement and manage, requiring skilled personnel for effective use and management.
  • Dependency on Cloud
    Being dependent on the cloud can be a disadvantage for utilities operating in regions with limited internet connectivity.
  • Customization
    Customization options may be limited, potentially leading to challenges when specific needs or requirements are not met.
  • Training and Onboarding
    Training and onboarding for new users might be necessary due to the platform’s complexity, adding to initial deployment timeframes.

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

Oracle DataRaker videos

+ Add

Analyze and predict transformer failure with Oracle DataRaker

Category Popularity

0-100% (relative to Amazon Kinesis and Oracle DataRaker)

Amazon Kinesis

Oracle DataRaker

Stream Processing
75 75%
Stream Processing
25% 25
Project Management
0 0%
Project Management
100% 100
Data Management
100 100%
Data Management
0% 0
Energy And Utilities Vertical Software
0 0%
Energy And Utilities Vertical Software
100% 100

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 Oracle DataRaker

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

Oracle DataRaker Reviews

We have no reviews of Oracle DataRaker yet.
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Social recommendations and mentions

Based on our record, Amazon Kinesis seems to be more popular. 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

Oracle DataRaker mentions (0)

We have not tracked any mentions of Oracle DataRaker yet. Tracking of Oracle DataRaker recommendations started around Mar 2021.

What are some alternatives?

When comparing Amazon Kinesis and Oracle DataRaker, you can also consider the following products

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

The PI System - With the PI System, OSIsoft customers have reduced costs, opened new revenue streams, extended equipment life, increased production capacity, and more.

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

ATLAS Energy Monitoring System - AtlasEVO Energy Management & Energy Monitoring Systems. Collect and analyse energy usage data (electric, gas, water etc) from any number of metering points.

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

GENERIS Platform - Meter Data Management

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