Kafdrop vs AKHQ vs Redpanda Console: Best Kafka UI Management Tools 2026

Managing Apache kafka clusters from the command line is tedious. You need a visual interface to browse topics, inspect messages, monitor consumer group lag, and manage the schema registry — without writing Kafka CLI commands for every single task. That’s exactly what self-hosted Kafka UI tools solve.

In this guide, we compare the three most popular open-source Kafka management web interfaces: Kafdrop, AKHQ, and Redpanda Console (formerly Kowl). Each runs as a docker container, connects to your Kafka brokers, and provides a browser-based dashboard for cluster operations.

Why You Need a Kafka UI

Apache Kafka ships with powerful CLI tools (kafka-topics.sh, kafka-console-consumer.sh, kafka-consumer-groups.sh), but they have significant limitations for day-to-day operations:

• No visual topic browsing — you can’t click through topics and browse messages in a structured way
• Consumer group monitoring is manual — you must run describe commands for each group to check lag
• Schema registry exploration requires separate tools — Confluent’s CLI doesn’t integrate with topic browsing
• No multi-cluster switching — managing multiple clusters means reconfiguring and reconnecting constantly
• Message inspection is painful — reading serialized Avro or Protobuf messages from the terminal is impractical

A web-based Kafka UI solves all of these. You connect once, see all topics and consumer groups at a glance, inspect messages with automatic deserialization, and switch between clusters with a dropdown selector.

If you’re evaluating Kafka distributions, check our Kafka vs Redpanda vs Pulsar comparison for the broader picture.

Quick Comparison Table

Kafdrop — Lightweight Kafka Web UI

Kafdrop is the most straightforward Kafka UI. It provides a clean, minimal web interface for browsing topics, viewing messages, and checking consumer group status. If you need a quick way to look at what’s happening in a single Kafka cluster, Kafdrop gets the job done with minimal configuration.

Key Features

• Topic browsing — list all topics, view partition details, and inspect message contents
• Consumer group monitoring — see consumer group state, member assignments, and lag per partition
• Schema registry integration — view registered schemas and their versions
• Automatic deserialization — decodes Avro, Protobuf, and JSON messages automatically
• Kerberos support — integrates with SASL/GSSAPI authentication
• Zero configuration for local clusters — just point it at a broker address

Docker Compose Deployment

Kafdrop includes a Docker Compose setup that bundles a Kafka broker alongside the UI for quick testing:

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version: "2"
services:
  kafdrop:
    image: obsidiandynamics/kafdrop
    restart: "no"
    ports:
      - "9000:9000"
    environment:
      KAFKA_BROKERCONNECT: "kafka:29092"
    depends_on:
      - "kafka"
  kafka:
    image: obsidiandynamics/kafka
    restart: "no"
    ports:
      - "2181:2181"
      - "9092:9092"
    environment:
      KAFKA_LISTENERS: "INTERNAL://:29092,EXTERNAL://:9092"
      KAFKA_ADVERTISED_LISTENERS: "INTERNAL://kafka:29092,EXTERNAL://localhost:9092"
      KAFKA_LISTENER_SECURITY_PROTOCOL_MAP: "INTERNAL:PLAINTEXT,EXTERNAL:PLAINTEXT"
      KAFKA_INTER_BROKER_LISTENER_NAME: "INTERNAL"

For production use against an existing Kafka cluster, you only need the Kafdrop service:

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services:
  kafdrop:
    image: obsidiandynamics/kafdrop:latest
    restart: unless-stopped
    ports:
      - "9000:9000"
    environment:
      KAFKA_BROKERCONNECT: "kafka-broker-01:9092,kafka-broker-02:9092"
      # Optional: Schema Registry
      SCHEMAREGISTRY_CONNECT: "http://schema-registry:8085"
      # Optional: SASL authentication
      KAFKA_PROPERTIES_SECURITY_PROTOCOL: "SASL_PLAINTEXT"
      KAFKA_PROPERTIES_SASL_MECHANISM: "SCRAM-SHA-256"
      KAFKA_PROPERTIES_SASL_JAAS_CONFIG: "org.apache.kafka.common.security.scram.ScramLoginModule required username=\"admin\" password=\"secret\";"

Limitations

Kafdrop’s simplicity is also its main limitation. It lacks multi-cluster support, Kafka Connect management, consumer group offset reset capabilities, and role-based access control. The message viewer is functional but doesn’t support advanced filtering or data masking. It’s best suited for development and staging environments where a single cluster needs basic monitoring.

AKHQ — Full-Featured Kafka Management Platform

AKHQ (formerly Kafka HQ) is the most feature-complete open-source Kafka UI. It manages topics, consumer groups, schema registry, Kafka Connect, and even supports ACL management. If you need a comprehensive Kafka management tool that handles the entire ecosystem, AKHQ is the strongest option.

Key Features

• Complete topic management — create, delete, and configure topics with partition and replication settings
• Consumer group operations — view lag, reset offsets to specific positions or timestamps
• Schema registry management — browse, create, and delete schema versions with compatibility checks
• Kafka Connect UI — manage connectors, view status, and browse connector configurations
• Multi-cluster support — configure multiple Kafka clusters and switch between them in the UI
• Authentication — supports LDAP, OIDC, and basic auth with role-based permissions
• Advanced message browsing — filter messages by key, value, timestamp, and header with SQL-like syntax
• Metrics dashboard — built-in charts for topic throughput, consumer lag, and broker health

Docker Compose Deployment

AKHQ ships with a comprehensive Docker Compose that includes Zookeeper, Kafka, Schema Registry, and Connect:

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volumes:
  zookeeper-data:
    driver: local
  zookeeper-log:
    driver: local
  kafka-data:
    driver: local

services:
  akhq:
    image: tchiotludo/akhq
    restart: unless-stopped
    environment:
      AKHQ_CONFIGURATION: |
        akhq:
          connections:
            docker-kafka-server:
              properties:
                bootstrap.servers: "kafka:9092"
              schema-registry:
                url: "http://schema-registry:8085"
              connect:
                - name: "connect"
                  url: "http://connect:8083"
    ports:
      - 8080:8080

  zookeeper:
    image: confluentinc/cp-zookeeper:latest
    restart: unless-stopped
    volumes:
      - zookeeper-data:/var/lib/zookeeper/data:Z
      - zookeeper-log:/var/lib/zookeeper/log:Z
    environment:
      ZOOKEEPER_CLIENT_PORT: '2181'

  kafka:
    image: confluentinc/cp-kafka:latest
    restart: unless-stopped
    volumes:
      - kafka-data:/var/lib/kafka/data:Z
    environment:
      KAFKA_BROKER_ID: '0'
      KAFKA_ZOOKEEPER_CONNECT: 'zookeeper:2181'
      KAFKA_ADVERTISED_LISTENERS: 'PLAINTEXT://kafka:9092'
      KAFKA_AUTO_CREATE_TOPICS_ENABLE: 'true'

For production with an existing cluster, deploy only the AKHQ service:

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services:
  akhq:
    image: tchiotludo/akhq:latest
    restart: unless-stopped
    ports:
      - "8080:8080"
    environment:
      AKHQ_CONFIGURATION: |
        akhq:
          connections:
            production-cluster:
              properties:
                bootstrap.servers: "prod-kafka-01:9092,prod-kafka-02:9092"
              schema-registry:
                url: "http://prod-schema-registry:8085"
              connect:
                - name: "prod-connect"
                  url: "http://prod-connect:8083"
              # Optional: LDAP authentication
              ldap:
                url: "ldap://ldap-server:389"
                base-dn: "ou=users,dc=example,dc=com"

When to Choose AKHQ

AKHQ is the right choice when you need a single tool to manage the entire Kafka ecosystem. Its Kafka Connect UI alone makes it valuable for teams running data pipelines. The multi-cluster support and LDAP/OIDC authentication make it suitable for production environments. If your team already uses tools like Debezium for change data capture, AKHQ gives you a unified UI to monitor both the CDC connectors and the underlying Kafka topics.

Redpanda Console — Modern Kafka UI with Enterprise Features

Redpanda Console (formerly known as Kowl) is a modern Kafka and Redpanda management UI built by Redpanda. Written in Go with a TypeScript frontend, it offers a polished experience with advanced features like data masking, time-travel debugging, and granular role-based access control.

Key Features

• Topic and message management — create topics, browse messages with automatic schema-based deserialization
• Advanced message filtering — regex-based search, JSONPath queries, and timestamp-based navigation
• Data masking — mask sensitive fields in messages using regex patterns or JSONPath rules
• Consumer group management — view lag details, reset offsets, and inspect group membership
• Schema registry — full schema registry browser with compatibility level management
• Kafka Connect — manage connectors and view their status
• Multi-cluster support — connect to multiple Kafka/Redpanda clusters simultaneously
• Role-based access control — fine-grained permissions for viewing, editing, and admin operations
• Authentication — OIDC (Okta, Google, GitHub), basic auth, and anonymous access modes
• Time-travel debugging — jump to any point in time and see what messages existed on a topic
• Low resource footprint — Go backend is lightweight compared to Java-based alternatives

Docker Compose Deployment

Redpanda Console doesn’t ship a bundled Kafka stack in its repository, making it easy to deploy alongside your existing infrastructure:

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services:
  console:
    image: docker.redpanda.com/redpandadata/console:latest
    restart: unless-stopped
    ports:
      - "8080:8080"
    environment:
      KAFKA_BROKERS: "kafka-01:9092,kafka-02:9092"
      # Optional: Schema Registry
      SCHEMAREGISTRY_ENABLED: "true"
      SCHEMAREGISTRY_URLS: "http://schema-registry:8085"
      # Optional: Kafka Connect
      CONNECT_ENABLED: "true"
      CONNECT_CLUSTERS: '[{"name":"connect-cluster","url":"http://connect:8083"}]'
      # Optional: Data masking rules
      TOPIC_DOCUMENTATION_ENABLED: "true"
    # Optional: Mount a YAML config file for advanced settings
    # volumes:
    #   - ./console-config.yaml:/etc/console/configs/config.yaml:ro

For a production setup with OIDC authentication and data masking:

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services:
  console:
    image: docker.redpanda.com/redpandadata/console:latest
    restart: unless-stopped
    ports:
      - "8080:8080"
    volumes:
      - ./console-config.yaml:/etc/console/configs/config.yaml:ro

# console-config.yaml:
# kafka:
#   brokers:
#     - "prod-kafka-01:9092"
#     - "prod-kafka-02:9092"
#     - "prod-kafka-03:9092"
#   sasl:
#     enabled: true
#     mechanism: SCRAM-SHA-256
#     username: "${KAFKA_USERNAME}"
#     password: "${KAFKA_PASSWORD}"
# login:
#   enabled: true
#   oidc:
#     enabled: true
#     clientId: "${OIDC_CLIENT_ID}"
#     clientSecret: "${OIDC_CLIENT_SECRET}"
#     issuerUrl: "https://auth.example.com/oidc"
# enterprise:
#   rbac:
#     enabled: true
#     roleBindings:
#       - metadata:
#           name: "developers"
#         subjects:
#           - kind: group
#             provider: OIDC
#             name: "dev-team"
#         roleName: "editor"
#         clusterRoles: ["kafka:acl.editor"]
# console:
#   messageRedaction:
#     enabled: true
#     rules:
#       - fieldName: "email"
#         regex: "[\\w.%+-]+@[\\w.-]+\\.[a-z]{2,}"
#         replacer: "[REDACTED]"

When to Choose Redpanda Console

Redpanda Console excels in enterprise environments where data privacy (masking), access control (RBAC), and developer experience (time-travel debugging) matter. The Go backend has a smaller memory footprint than Java-based alternatives, making it a good fit for resource-constrained environments. If you’re running Redpanda (the Kafka-compatible streaming engine), Console is the native choice with first-class support.

Feature Deep Dive: Message Inspection

All three tools support message browsing, but the experience differs significantly:

Kafdrop displays messages in a simple table with key, value, headers, and timestamp columns. It auto-detects Avro and Protobuf schemas and deserializes accordingly. The interface is functional but lacks filtering — you scroll through all messages on a partition.

AKHQ adds SQL-like filtering: you can search messages by key pattern, value content, timestamp range, and header values. The message viewer supports hex, JSON, and raw text formats. You can also navigate to a specific offset or timestamp, which is invaluable for debugging.

Redpanda Console goes further with regex-based value search and JSONPath queries. The time-travel feature lets you specify a timestamp and see all messages that existed on a topic at that point — effectively a “rewind” button for your event stream. Combined with data masking rules, this makes it safe to browse production data without exposing sensitive fields.

Feature Deep Dive: Consumer Group Management

Consumer group monitoring is critical for Kafka operations. All three tools display consumer group state, member assignments, and per-partition lag, but operational capabilities vary:

• Kafdrop provides read-only visibility. You can see which consumers are active, their assigned partitions, and current lag, but you cannot modify offsets or pause/resume groups.
• AKHQ allows offset resets — you can move a consumer group to the earliest offset, latest offset, a specific timestamp, or a specific offset value. This is essential for replaying events after a bug fix.
• Redpanda Console offers the same offset reset capabilities plus group-level state management and member inspection with detailed metadata.

Deployment Architecture

All three tools follow the same basic pattern: a stateless web application that connects to Kafka brokers over the network. There’s no database to manage — the UI reads directly from Kafka and caches metadata in memory.

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┌──────────────┐     HTTP      ┌──────────────────┐
│   Browser    │ ────────────▶ │   Kafka UI Tool  │
└──────────────┘               └────────┬─────────┘
                                        │ Kafka Protocol (TCP 9092)
                                        ▼
                               ┌──────────────────┐
                               │   Kafka Brokers  │
                               └──────────────────┘

For production deployments:

-nginxverse proxy** — place Nginx, Traefik, or Caddy in front for TLS termination and authentication

• Resource allocation — 256MB–512MB RAM is sufficient for most clusters; message-heavy usage may need 1GB
• Network access — the UI needs TCP connectivity to all Kafka brokers and the schema registry
• Scaling — since these are stateless, you can run multiple instances behind a load balancer

Which Should You Choose?

Choose Kafdrop if:

• You need a quick, no-fuss way to browse topics and messages
• You’re running a single Kafka cluster
• You want minimal configuration overhead
• Your team doesn’t need consumer group offset management or Kafka Connect UI

Choose AKHQ if:

• You need comprehensive Kafka ecosystem management (topics + consumers + schema registry + Connect)
• You manage multiple clusters and need unified access
• LDAP/OIDC authentication is required
• You need consumer group offset reset capabilities

Choose Redpanda Console if:

• Data masking is a compliance requirement
• You need role-based access control with fine-grained permissions
• You want the best developer experience (time-travel, JSONPath search)
• You prefer a lightweight Go backend over Java
• You’re running Redpanda alongside or instead of Apache Kafka

For related reading, see our event sourcing architecture guide which covers when to use Kafka versus alternatives like EventStoreDB and Pulsar.

FAQ

Can I run multiple Kafka UI tools simultaneously?

Yes. All three tools are stateless and connect to Kafka as regular consumers/producers. You can run Kafdrop for quick topic browsing and AKHQ for consumer group management at the same time. They don’t conflict with each other or impact Kafka performance beyond normal consumer group overhead.

Does Kafdrop support Kafka Connect management?

No. Kafdrop focuses on topic browsing, message viewing, and consumer group monitoring. It does not include a Kafka Connect UI. If you need to manage Connect connectors, use AKHQ or Redpanda Console instead.

How do I enable TLS and SASL authentication for these tools?

All three tools support TLS and SASL. For Kafdrop, set KAFKA_PROPERTIES_SECURITY_PROTOCOL and related properties as environment variables. For AKHQ, configure TLS and SASL within the AKHQ_CONFIGURATION YAML block. For Redpanda Console, use the kafka.sasl and kafka.tls sections in the YAML config file. See the Docker Compose examples in each tool’s section above for specific configurations.

Can I use these tools with Confluent Cloud or MSK?

Yes. All three tools connect to any Kafka-compatible broker, including managed services like Confluent Cloud, Amazon MSK, and Azure Event Hubs (with Kafka endpoint). You’ll need to configure SASL authentication with the credentials provided by your cloud provider and ensure network connectivity (VPC peering or public endpoints).

What is the difference between Redpanda Console and Kowl?

Redpanda Console is the new name for Kowl. After Redpanda acquired the Kowl project, it was rebranded as Redpanda Console. The codebase remains open-source and the core features are the same. Newer releases include additional enterprise features like RBAC and data masking.

Which Kafka UI tool has the smallest resource footprint?

Redpanda Console has the smallest footprint because it’s built with Go — the binary is ~30MB and typically uses 100–200MB of RAM. Kafdrop and AKHQ are Java-based and require a JVM, using 300–500MB of RAM at idle. For resource-constrained environments, Redpanda Console is the most efficient choice.

How do I back up the configuration for these tools?

Since these tools are stateless, there’s no database to back up. Configuration is defined entirely through environment variables and YAML config files. Simply version-control your Docker Compose files and configuration YAML in Git. Consumer group offset resets and topic configurations made through the UI are applied directly to Kafka and are persisted by the Kafka brokers themselves.