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Tableau VS Apache Kafka

Compare Tableau VS Apache Kafka and see what are their differences

Draxlr
Turn SQL Data into Decisions. Build professional dashboards and data visualizations without technical expertise. Easily embed analytics anywhere, receive automated alerts, and discover AI-powered insights all through a straightforward interface. featured
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Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Tableau logo Tableau

Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.

Apache Kafka logo Apache Kafka

Apache Kafka is an open-source message broker project developed by the Apache Software Foundation written in Scala.
  • Tableau Landing page
    Landing page //
    2023-10-18
  • Apache Kafka Landing page
    Landing page //
    2022-10-01

Tableau features and specs

  • User-Friendly Interface
    Tableau offers an intuitive drag-and-drop interface that allows users to create visualizations and dashboards easily, even without extensive technical knowledge.
  • Data Connectivity
    Tableau supports a wide range of data sources including databases, spreadsheets, cloud services, and more, allowing for flexible data integration.
  • Advanced Analytics
    Advanced analytical capabilities, including real-time analytics, trend analysis, and predictive analytics, help users gain deeper insights from their data.
  • Community and Support
    A large, active user community provides a wealth of resources including forums, tutorials, and user groups for support and knowledge sharing.
  • Visualization Quality
    Tableau offers high-quality visualizations with customizable options that make it easier to create compelling reports and dashboards.

Possible disadvantages of Tableau

  • Cost
    Tableau can be expensive, especially for small businesses or individual users, with its various licensing and subscription fees.
  • Performance Issues
    For very large datasets or complex calculations, Tableau can experience performance slowdowns, affecting the efficiency and user experience.
  • Steep Learning Curve for Advanced Features
    While basic features are easy to use, mastering advanced functionalities can require a significant learning curve and technical expertise.
  • Customization Limitations
    Although Tableau is highly customizable, some users find it lacks flexibility when it comes to very specific or unique customization requirements.
  • Export Limitations
    Exporting visualizations and dashboards to formats like PDF or PowerPoint can sometimes be restrictive, limiting the ways reports are shared.

Apache Kafka features and specs

  • High Throughput
    Kafka is capable of handling thousands of messages per second due to its distributed architecture, making it suitable for applications that require high throughput.
  • Scalability
    Kafka can easily scale horizontally by adding more brokers to a cluster, making it highly scalable to serve increased loads.
  • Fault Tolerance
    Kafka has built-in replication, ensuring that data is replicated across multiple brokers, providing fault tolerance and high availability.
  • Durability
    Kafka ensures data durability by writing data to disk, which can be replicated to other nodes, ensuring data is not lost even if a broker fails.
  • Real-time Processing
    Kafka supports real-time data streaming, enabling applications to process and react to data as it arrives.
  • Decoupling of Systems
    Kafka acts as a buffer and decouples the production and consumption of messages, allowing independent scaling and management of producers and consumers.
  • Wide Ecosystem
    The Kafka ecosystem includes various tools and connectors such as Kafka Streams, Kafka Connect, and KSQL, which enrich the functionality of Kafka.
  • Strong Community Support
    Kafka has strong community support and extensive documentation, making it easier for developers to find help and resources.

Possible disadvantages of Apache Kafka

  • Complex Setup and Management
    Kafka's distributed nature can make initial setup and ongoing management complex, requiring expert knowledge and significant administrative effort.
  • Operational Overhead
    Running Kafka clusters involves additional operational overhead, including hardware provisioning, monitoring, tuning, and scaling.
  • Latency Sensitivity
    Despite its high throughput, Kafka may experience increased latency in certain scenarios, especially when configured for high durability and consistency.
  • Learning Curve
    The concepts and architecture of Kafka can be difficult for new users to grasp, leading to a steep learning curve.
  • Hardware Intensive
    Kafka's performance characteristics often require dedicated and powerful hardware, which can be costly to procure and maintain.
  • Dependency Management
    Managing Kafka's dependencies and ensuring compatibility between versions of Kafka, Zookeeper, and other ecosystem tools can be challenging.
  • Limited Support for Small Messages
    Kafka is optimized for large throughput and can be inefficient for applications that require handling a lot of small messages, where overhead can become significant.
  • Operational Complexity for Small Teams
    Smaller teams might find the operational complexity and maintenance burden of Kafka difficult to manage without a dedicated operations or DevOps team.

Tableau videos

+ Add

Power BI vs Tableau 🔥 5 Factors to Choose a Winner

More videos:

  • Review - What is Tableau Desktop? | A Tableau Desktop Overview
  • Demo - Tableau Software Demo

Apache Kafka videos

+ Add

Apache Kafka Tutorial | What is Apache Kafka? | Kafka Tutorial for Beginners | Edureka

More videos:

  • Review - Apache Kafka - Getting Started - Kafka Multi-node Cluster - Review Properties
  • Review - 4. Apache Kafka Fundamentals | Confluent Fundamentals for Apache Kafka®
  • Review - Apache Kafka in 6 minutes
  • Review - Apache Kafka Explained (Comprehensive Overview)
  • Review - 2. Motivations and Customer Use Cases | Apache Kafka Fundamentals

Category Popularity

0-100% (relative to Tableau and Apache Kafka)

Tableau

Apache Kafka

Data Dashboard
100 100%
Data Dashboard
0% 0
Stream Processing
0 0%
Stream Processing
100% 100
Data Visualization
100 100%
Data Visualization
0% 0
Data Integration
0 0%
Data Integration
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 Tableau and Apache Kafka

Tableau Reviews

Explore 7 Tableau Alternatives for Data Visualization and Analysis
Welcome to our complete reference, Tableau Alternatives for Data Visualization and Analysis. In this fast-changing digital age, data visualization and analysis have become critical for making informed decisions and strategies. Tableau is a well-known product that has had a considerable impact in this sector. Its user-friendly interface and powerful capabilities have made it...
Source: www.draxlr.com
Explore 6 Metabase Alternatives for Data Visualization and Analysis
To find the best Metabase alternative for your business, start by listing your specific requirements, such as customer support, data integrations, visualization options, user access controls, and budget. Compare these needs with the features of other BI tools like Draxlr, Tableau, Power BI, Looker, or Holistics. Once you've identified a few suitable options, take advantage...
Source: www.draxlr.com
5 best Looker alternatives
Tableau: Tableau is the earliest BI tools built to solve data problems, which means it has a lot of community support for all your queries and can lack what the new-age tools have and are building.
Source: www.draxlr.com
10 Best Alternatives to Looker in 2024
Tableau: Renowned for its powerful visualization capabilities, Tableau enables users to create highly intuitive and interactive dashboards. Favored for its user-friendly interface, Tableau effectively handles large datasets, making it a top choice for data visualization.
Source: www.sigmacomputing.com
6 Best Looker alternatives
Pricing: Looker is typically more expensive than Tableau – but if you’re a growing company with increasing user numbers, Tableau can also get pricey.
Source: trevor.io

Apache Kafka Reviews

Best ETL Tools: A Curated List
Debezium is an open-source Change Data Capture (CDC) tool that originated from RedHat. It leverages Apache Kafka and Kafka Connect to enable real-time data replication from databases. Debezium was partly inspired by Martin Kleppmann’s "Turning the Database Inside Out" concept, which emphasized the power of the CDC for modern data pipelines.
Source: estuary.dev
Best message queue for cloud-native apps
If you take the time to sort out the history of message queues, you will find a very interesting phenomenon. Most of the currently popular message queues were born around 2010. For example, Apache Kafka was born at LinkedIn in 2010, Derek Collison developed Nats in 2010, and Apache Pulsar was born at Yahoo in 2012. What is the reason for this?
Source: docs.vanus.ai
Are Free, Open-Source Message Queues Right For You?
Apache Kafka is a highly scalable and robust messaging queue system designed by LinkedIn and donated to the Apache Software Foundation. It's ideal for real-time data streaming and processing, providing high throughput for publishing and subscribing to records or messages. Kafka is typically used in scenarios that require real-time analytics and monitoring, IoT applications,...
Source: blog.iron.io
10 Best Open Source ETL Tools for Data Integration
It is difficult to anticipate the exact demand for open-source tools in 2023 because it depends on various factors and emerging trends. However, open-source solutions such as Kubernetes for container orchestration, TensorFlow for machine learning, Apache Kafka for real-time data streaming, and Prometheus for monitoring and observability are expected to grow in prominence in...
Source: testsigma.com
11 Best FREE Open-Source ETL Tools in 2024
Apache Kafka is an Open-Source Data Streaming Tool written in Scala and Java. It publishes and subscribes to a stream of records in a fault-tolerant manner and provides a unified, high-throughput, and low-latency platform to manage data.
Source: hevodata.com

Social recommendations and mentions

Based on our record, Apache Kafka seems to be a lot more popular than Tableau. While we know about 143 links to Apache Kafka, we've tracked only 8 mentions of Tableau. 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.

Tableau mentions (8)

  • Tableau Certified Data Analyst Exam Readiness
    Hey everyone, I'm interested in taking the Tableau Certified Data Analyst Exam Readiness course through tableau.com to prepare and get Tableau certified. I had some questions about the course, such as are the videos pre recorded or in person, do you have access to the material once the 90 days expire, and I was also wondering if anyone had input/advice for this course. Thanks! Source: almost 2 years ago
  • Where to publish knowledge sharing on Tableau reverse engineering and data dictionary generation?
    Could anyone recommend what media I should approach to publish my work (internet or print). I could try the Tableau forum in tableau.com but it's not very active + Tableau may be unappreciative as my work overlaps with their (pricey) data management solution. Plus it needs to be some high visibility / reputable media to count for my career development. Any recommendations welcome thanks!!! Source: over 2 years ago
  • I have huge loads of data in Redshift. How can I make this available to end-users after performing few procs and queries? It should be available online.
    Tableau public: tableau.com. Big player but your data will be made public and not really user-friendly data model. Source: about 3 years ago
  • What tips do you have on evaluating various BI tools for business needs? What are the essential criteria's you would include when evaluating different tools? The goal is to have an unbiased, objective approach.
    For example, we have a project to compare Tableau, Power BI, and InetSoft. The need for strong pagination-based email delivery eliminated Tableau. AWS's Linux instance is the targeted platform which makes Power BI less than ideal. Source: about 3 years ago
  • Anyone go into Data Analytics after this program?
    I just started learning Tableau because our dept is transitioning into Tableau from Power BI. Since I already have years of experience with Power BI I just went over their tutorials from tableau.com and got onboarded pretty quick. I'm still learning it but I'm at least able to build out reports and get things done. Its not too difficult to pickup one BI tool when you have experience with another. Source: over 3 years ago
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Apache Kafka mentions (143)

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What are some alternatives?

When comparing Tableau and Apache Kafka, you can also consider the following products

Microsoft Power BI - BI visualization and reporting for desktop, web or mobile

RabbitMQ - RabbitMQ is an open source message broker software.

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.

Apache ActiveMQ - Apache ActiveMQ is an open source messaging and integration patterns server.

Sisense - The BI & Dashboard Software to handle multiple, large data sets.

StatCounter - StatCounter is a simple but powerful real-time web analytics service that helps you track, analyse and understand your visitors so you can make good decisions to become more successful online.

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