DZone
Thanks for visiting DZone today,
Edit Profile
  • Manage Email Subscriptions
  • How to Post to DZone
  • Article Submission Guidelines
Sign Out View Profile
  • Post an Article
  • Manage My Drafts
Over 2 million developers have joined DZone.
Log In / Join
Refcards Trend Reports
Events Video Library
Refcards
Trend Reports

Events

View Events Video Library

Related

  • Event-Driven Pipelines With Apache Pulsar and Go
  • Contract-First Integration: Building Scalable Systems With Flyway, OpenAPI, and Kafka
  • Kafka and Spark Structured Streaming in Enterprise: The Patterns That Hold Up Under Pressure
  • Exactly-Once Processing: Myth vs Reality

Trending

  • Feature Flag Debt: Performance Impact in Enterprise Applications
  • When Snowflake Lies to You: Understanding False Failures in dbt Pipelines
  • Building a High-Throughput Distributed Sequence Generator Using the Hi-Lo Algorithm
  • The Hidden Cost of AI Tokens: Engineering Patterns for 10x Resource Efficiency
  1. DZone
  2. Data Engineering
  3. Big Data
  4. Top 10 Kafka Features: Reasons Behind the Popularity of Apache Kafka

Top 10 Kafka Features: Reasons Behind the Popularity of Apache Kafka

Apache Kafka is one of the most popular tools in the big data world. Read on to get a nice high-level overview explaining why.

By 
Shailna Patidar user avatar
Shailna Patidar
·
Sep. 04, 18 · Opinion
Likes (19)
Comment
Save
Tweet
Share
22.5K Views

Join the DZone community and get the full member experience.

Join For Free

1. Objective

Today, we will discuss all the features of Kafka, like scalability, reliability, durability, that show why Kafka is so popular. We will discuss each features in detail. But before that, let’s understand what Kafka is. 

2. What Is Apache Kafka?

Apache Kafka is a distributed publish-subscribe messaging system for handling a high volume of data that enables us to pass messages from one end-point to another. It is suitable for both offline and online message consumption. Moreover, in order to prevent data loss, Kafka messages are persisted on disk and replicated within the cluster. In addition, it is built on top of the ZooKeeper synchronization service. While it comes to real-time streaming data analysis, it can also integrate very well with Apache Storm and Spark. There are many more features of Apache Kafka. Let’s discuss them in detail.

3. Top 10 Apache Kafka Features

a. Scalability

Apache Kafka can handle scalability in all the four dimensions, i.e. event producers, event processors, event consumers, and event connectors. In other words, Kafka scales easily without downtime.

b. High-Volume

Kafka can work with a huge volume of data streams, easily.

c. Data Transformations

Kafka offers provisions for deriving new data streams using the data streams from producers.

d. Fault Tolerance

Kafka clusters can handle failures with the masters and databases.

e. Reliability

Since Kafka is distributed, partitioned, replicated, and fault tolerant, it is very reliable.

f. Durability

It is durable because Kafka uses Distributed commit logs, which means messages persist on disk as fast as possible.

g. Performance

For both publishing and subscribing messages, Kafka has high throughput. Even if many TBs of messages are stored, it maintains stable performance.

h. Zero Downtime

Kafka is very fast and guarantees zero downtime and zero data loss.

i. Extensibility

There are many ways by which applications can plug in and make use of  Kafka. In addition, Kafka offers ways to write new connectors as needed.

j. Replication

By using ingest pipelines, it can replicate events.

4. Conclusion

We have seen the best Apache Kafka features, that make it very popular. However, if you want to ask any query regarding these features of Kafka, feel free to ask through the comment tab. Hope this helps!

kafka trends

Published at DZone with permission of Shailna Patidar. See the original article here.

Opinions expressed by DZone contributors are their own.

Related

  • Event-Driven Pipelines With Apache Pulsar and Go
  • Contract-First Integration: Building Scalable Systems With Flyway, OpenAPI, and Kafka
  • Kafka and Spark Structured Streaming in Enterprise: The Patterns That Hold Up Under Pressure
  • Exactly-Once Processing: Myth vs Reality

Partner Resources

×

Comments

The likes didn't load as expected. Please refresh the page and try again.

  • RSS
  • X
  • Facebook

ABOUT US

  • About DZone
  • Support and feedback
  • Community research

ADVERTISE

  • Advertise with DZone

CONTRIBUTE ON DZONE

  • Article Submission Guidelines
  • Become a Contributor
  • Core Program
  • Visit the Writers' Zone

LEGAL

  • Terms of Service
  • Privacy Policy

CONTACT US

  • 3343 Perimeter Hill Drive
  • Suite 215
  • Nashville, TN 37211
  • [email protected]

Let's be friends:

  • RSS
  • X
  • Facebook