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Salt VS Apache Kafka

Compare Salt VS Apache Kafka and see what are their differences

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Salt logo Salt

Fast, scalable and flexible software for data center automation

Apache Kafka logo Apache Kafka

Apache Kafka is an open-source message broker project developed by the Apache Software Foundation written in Scala.
  • Salt Landing page
    Landing page //
    2023-02-05
  • Apache Kafka Landing page
    Landing page //
    2022-10-01

Salt features and specs

  • Scalability
    Salt is designed to be highly scalable, suitable for managing thousands of servers with ease.
  • Speed
    Salt's event-driven architecture allows for very fast data collection and task execution, enabling near real-time interactions.
  • Flexibility
    Salt provides a variety of options for remote execution, configuration management, and monitoring, catering to various needs and workflows.
  • Community and Support
    Salt has a vibrant community and strong support, which helps in troubleshooting and gaining insights from the collective expertise of its users.
  • Automation Capabilities
    Salt excels in automating complex workflows and orchestrations, allowing users to create detailed and intricate automation scripts.

Possible disadvantages of Salt

  • Complexity
    Salt can be complex to set up and configure, especially for new users who are not familiar with its architecture and components.
  • Documentation Issues
    While Salt has extensive documentation, some users find it lacking in clarity or organization, making it challenging to find specific information.
  • Resource Intensive
    Salt can be resource-intensive, potentially requiring significant system resources, especially when managing a large number of nodes.
  • Steep Learning Curve
    The multitude of features and functionalities offered by Salt might result in a steep learning curve for new users.
  • Overhead
    The use of Salt's extensive features can sometimes lead to overhead, making it potentially cumbersome for simpler automation tasks.

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.

Salt videos

+ Add

Salt movie review

More videos:

  • Review - Salt - Movie Review
  • Review - 5 Best Salts For Cooking...And One To Avoid - Salt Grocery Haul

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 Salt and Apache Kafka)

Salt

Apache Kafka

DevOps Tools
100 100%
DevOps Tools
0% 0
Stream Processing
0 0%
Stream Processing
100% 100
Product Deployment
100 100%
Product Deployment
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 Salt and Apache Kafka

Salt Reviews

Ansible overtakes Chef and Puppet as the top cloud configuration management tool
Breaking these results down year-over-year, use of Ansible grew from 36% in 2018 to 41% in 2019--surpassing Chef, which grew from 36% to 37%, as well as Puppet, which grew from 34% to 37%. Rounding out the list is Terraform, which experienced a jump from 20% to 31%, and Salt, which increased in usage from 13% to 18%.
Source: www.techrepublic.com

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 more popular. It has been mentiond 144 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.

Salt mentions (0)

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

Apache Kafka mentions (144)

View more

What are some alternatives?

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

Ansible - Radically simple configuration-management, application deployment, task-execution, and multi-node orchestration engine

RabbitMQ - RabbitMQ is an open source message broker software.

Chef - Automation for all of your technology. Overcome the complexity and rapidly ship your infrastructure and apps anywhere with automation.

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.

Puppet Enterprise - Get started with Puppet Enterprise, or upgrade or expand.

Histats - Start tracking your visitors in 1 minute!

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