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KafkaCenter

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KafkaHQ

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KafkaHQ vs KafkaCenter: What are the differences?

Developers describe KafkaHQ as "Kafka GUI for topics, topics data, consumers group, schema registry, connect and more". It is a Kafka GUI for topics, topics data, consumers group, schema registry, connect and more. It works with modern Kafka cluster. On the other hand, KafkaCenter is detailed as "A unified one-stop platform for Kafka cluster management and maintenance". It is a unified one-stop platform for Kafka cluster management and maintenance, producer / consumer monitoring, and use of ecological components.

KafkaHQ and KafkaCenter can be primarily classified as "Kafka" tools.

Some of the features offered by KafkaHQ are:

  • Works with modern Kafka cluster (1.0+)
  • Connection on standard or ssl, sasl cluster
  • Multi cluster

On the other hand, KafkaCenter provides the following key features:

  • View kafka cluster list and monitoring information
  • Users can view their own topics in this module, apply for new topics, mock and consumption data
  • Users can view the production and consumption of topics in this module, and set warning information for consumption delays

KafkaHQ and KafkaCenter are both open source tools. It seems that KafkaHQ with 1.34K GitHub stars and 133 forks on GitHub has more adoption than KafkaCenter with 536 GitHub stars and 62 GitHub forks.

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What is KafkaCenter?

It is a unified one-stop platform for Kafka cluster management and maintenance, producer / consumer monitoring, and use of ecological components.

What is KafkaHQ?

It is a Kafka GUI for topics, topics data, consumers group, schema registry, connect and more. It works with modern Kafka cluster.

Need advice about which tool to choose?Ask the StackShare community!

What tools integrate with KafkaCenter?
What tools integrate with KafkaHQ?
What are some alternatives to KafkaCenter and KafkaHQ?
MySQL
The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.
PostgreSQL
PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.
MongoDB
MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
Redis
Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.
Amazon S3
Amazon Simple Storage Service provides a fully redundant data storage infrastructure for storing and retrieving any amount of data, at any time, from anywhere on the web
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