Software Alternatives, Accelerators & Startups

Analytics Canvas VS Amazon Kinesis Firehose

Compare Analytics Canvas VS Amazon Kinesis Firehose and see what are their differences

Analytics Canvas logo Analytics Canvas

Analytics Canvas is a data management platform with a specific focus on Google data tools, enabling self-serve data preparation and automation for those working with Analytics, Ads, Search Console, Sheets, BigQuery, Data Studio and more.

Amazon Kinesis Firehose logo Amazon Kinesis Firehose

Amazon Kinesis Firehose can capture, transform, and load streaming data into AWS.
  • Analytics Canvas Landing page
    Landing page //
    2023-09-11
  • Amazon Kinesis Firehose Landing page
    Landing page //
    2023-04-12

Analytics Canvas

$ Details
paid Free Trial $49.0 / Monthly
Platforms
Web Windows REST API

Analytics Canvas features and specs

No features have been listed yet.

Amazon Kinesis Firehose features and specs

  • Managed Service
    Amazon Kinesis Firehose is a fully managed service, which means it eliminates the operational overhead of managing and scaling infrastructure.
  • Real-time Processing
    It provides real-time data streaming capabilities, allowing for near-instantaneous processing and analysis of incoming data.
  • Seamless Integration
    Firehose integrates seamlessly with other AWS services like S3, Redshift, and Elasticsearch, making it easy to store and analyze data.
  • Automatic Scaling
    The service automatically scales to match the throughput of your data streams, ensuring consistent performance without manual intervention.
  • Data Transformation
    It provides built-in data transformation capabilities using AWS Lambda, allowing you to transform or enrich data before delivery.

Possible disadvantages of Amazon Kinesis Firehose

  • Cost
    While convenient, using Firehose can become expensive, especially with larger volumes of data or complex transformations.
  • Latency
    There might be slight latency involved in the data delivery process, which could be a concern for applications requiring ultra-low latency.
  • Dependency on AWS Ecosystem
    Firehose is tightly integrated with the AWS ecosystem, which could be a limitation if your architecture involves services outside of AWS.
  • Limited Customization
    As a managed service, users have limited control over the underlying infrastructure, which might be restrictive for those needing highly customized solutions.
  • Learning Curve
    New users might face a learning curve when getting started, especially if unfamiliar with AWS and its specific terminologies and best practices.

Analytics Canvas videos

Overview of Analytics Canvas Online

More videos:

  • Review - What is Analytics Canvas

Amazon Kinesis Firehose videos

Introduction to Amazon Kinesis Firehose

More videos:

  • Review - Stream Data Analytics with Amazon Kinesis Firehose and Redshift

Category Popularity

0-100% (relative to Analytics Canvas and Amazon Kinesis Firehose)
Data Dashboard
51 51%
49% 49
Data Management
54 54%
46% 46
Data Warehousing
54 54%
46% 46
Data Visualization
100 100%
0% 0

User comments

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Social recommendations and mentions

Based on our record, Amazon Kinesis Firehose seems to be more popular. It has been mentiond 6 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.

Analytics Canvas mentions (0)

We have not tracked any mentions of Analytics Canvas yet. Tracking of Analytics Canvas recommendations started around Mar 2021.

Amazon Kinesis Firehose mentions (6)

  • What is an event-driven architecture and why storing events is important ?
    First, you may not know the Kinesis Data Firehose service. Here's the AWS definition: Amazon Kinesis Data Firehose is an Extract, Transform, and Load (ETL) service that captures, transforms, and reliably delivers streaming data to data lakes, data stores, and analytics services. (https://aws.amazon.com/kinesis/data-firehose/). - Source: dev.to / about 2 years ago
  • Serverless Event Driven AI as a Service
    As you can see in the diagram, we are feeding all events from Event Bus via a catch-all rule into Kinesis Data Firehose. Firehose is a fully managed service that streams into specific destinations like Data Warehouses or Data Lakes. Unlike it's bigger brother of using Kinesis Data Streams directly, there are no setting up of shards and it's mostly configuration free. We are only defining a buffer interval which is... - Source: dev.to / over 2 years ago
  • Logging EventBridge events to S3 with Firehose
    When using EventBridge I always log all events to an S3 bucket for auditing, analytics and debugging purposes. A super easy method to do this is to create a Kinesis Data Firehose stream and create a rule that captures all events that points to the Firehose stream. The Firehose stream can then flush the events on S3 in an interval/size of choice based on configuration. - Source: dev.to / over 2 years ago
  • S3 Isn't Getting Cheaper
    Have you looked at Kinesis Firehose? It was pretty much build for this use case although you will still need to see if you can define a partitioning scheme probably in combination with an S3 Select query to meet your query requirements. https://aws.amazon.com/kinesis/data-firehose/?nc=sn&loc=0. - Source: Hacker News / almost 3 years ago
  • Advice on S3 Application
    Is continuous backup important ? e.g. If the stuff fails for one day and you lose that day's upload is that ok? Do you want it to push updates more frequently than once a day? If you want to continuously push updates then Kinesis Firehose might be worth looking into. Source: over 3 years ago
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What are some alternatives?

When comparing Analytics Canvas and Amazon Kinesis Firehose, you can also consider the following products

Lavastorm Analytics - Lavastorm is the agile data management and analytics solution.

Data Scientist Workbench - A web-based notebook that enables interactive data analytics.

Talend Data Preparation - Talend Data Preparation combines intuitive self-service data preparation and data curation tools with data integration to accelerate data usage across the organization.

Wealthport - Wealthport provides solutions to automatically clean, integrate and segment the data using artificial intelligence.

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.