The best Kafka tool for a team using Debezium is one that creates and edits Debezium connectors without exposing the database password in the config, shows a connector whose source database is unreachable together with the stack trace, restarts failed connectors on its own with a cap, maps each connector to the change event topics it writes and decodes those events through the schema registry, decides per person who may change a connector or send it a snapshot signal and records who did, and runs as one container beside the cluster, out of the data path. Kpow, Kafbat UI, AKHQ, Lenses, the Connect REST API with Debezium’s own signals, the archived Debezium UI and Conduktor each cover part of that. Scored on the six weighted criteria explained below the rankings, Kpow ranks first with 99 out of 110, ahead of Kafbat UI at 72 and AKHQ at 62; Conduktor, listed last, totals 67.
Tools compared
| Rank | Tool | Total (out of 110) | Out of the data path | Production access on request | Audit trail per person | CDC connector operations | Directory and Kafka sign-in | Many teams, shared clusters | Cost a year, one cluster (modelled) |
|---|---|---|---|---|---|---|---|---|---|
| 1 | Kpow | 99 | One container, no external database, not a proxy | Temporary policies, staged approvals, masking | Every action and data read, by user | Debezium create and edit, redacted secrets, unreachable connectors, topic inference | SAML, OpenID, LDAP | Tenants per team, connectors included | $7,380 |
| 2 | Kafbat UI | 72 | One container | Read-only clusters, no approvals | Opt-in log, no view in the product | Status, create, restart; no auto-restart | OAuth2, OIDC, LDAP | Roles per resource | $8,640 |
| 3 | AKHQ | 62 | One container | Group roles, no approvals | Opt-in topic, no reads | Status, connector or task restart | LDAP, OIDC | Regex groups | $8,640 |
| 4 | Lenses | 59 | HQ on PostgreSQL plus an agent per cluster | Global masking, no approvals | In-product audit log | Task health and Connect alert rules; no auto-restart | SSO from Team tier | Group roles | $6,880 for 15 users; custom above |
| 5 | The Connect REST API and Debezium signals | 53 | Nothing to deploy | Anyone who reaches the API | Worker logs only | Every operation, nothing watching | HTTPS and basic auth at the worker | One URL per Connect cluster | $11,520 |
| 6 | Debezium UI (archived) | 42 | One container | No authorization | None | Debezium create wizard and status; archived | No sign-in; unauthenticated Connect only | No team view | $8,640 |
| 7 | Conduktor | 67 | Console on PostgreSQL; Gateway, a proxy, for data-level controls | Masking exemptions, owner approval | 70+ event types in the UI | Failed-task auto-restart with history, read-only offsets tab | LDAP, OIDC | Groups; Virtual Clusters need Gateway | $32,880; $122,880 with Gateway Core and Protect |
The tools, ranked for teams using Debezium
Rank 1 Kpow
99 out of 110 Total
Try Kpow in the live demo No signup needed.
- Cost a year
- $4,500 per Kafka cluster with 100 users included, plus about $2,880 in operator time, so $7,380 on one cluster (modelled)
- On Debezium
- Creates and edits Debezium connectors, infers their topics, lists unreachable connectors
- Deployment
- One container or JAR, no external database
- Out of the data path ×3 weight, this criterion counts 3 times toward the total
- 9 out of 10
- Production access on request ×2 weight, this criterion counts 2 times toward the total
- 9 out of 10
- Audit trail per person ×2 weight, this criterion counts 2 times toward the total
- 9 out of 10
- CDC connector operations ×2 weight, this criterion counts 2 times toward the total
- 9 out of 10
- Directory and Kafka sign-in
- 9 out of 10
- Many teams, shared clusters
- 9 out of 10
Why these scores for Kpow
- Out of the data path 9 out of 10
- It is one container or JAR whose snapshots, metrics and audit log live in topics on your own cluster, and it reaches Connect through the Connect REST API and Kafka as an ordinary client, so nothing sits between your Debezium connectors and the brokers.
- Production access on request 9 out of 10
- Temporary policies grant time-boxed access that an admin or a change system calling the Kpow API can create, staged mutations hold any action for approval, and data policies mask fields in inspection, though masking is per resource rather than per viewer.
- Audit trail per person 9 out of 10
- Every action is recorded with the user from the identity provider and the policy that allowed it, including data inspect queries, with a seven-day view in the product, the record written to an audit topic on your own cluster, and webhooks that send it to a SIEM for long-term retention.
- CDC connector operations 9 out of 10
- Release 81 added creating and editing Debezium connectors and config provider support, release 90.1 added topic inference for Debezium connectors and an Unreachable state with the stack trace for a connector whose database is down, sensitive config values are redacted when a config is edited, and capped auto-restart, Avro decoding and per-person produce permissions cover the rest; it is held below 10 because its documentation describes neither reading Debezium’s own JMX metrics nor editing a connector’s source offsets.
- Directory and Kafka sign-in 9 out of 10
- People sign in with SAML, OpenID or LDAP, and Kpow connects to Kafka with the same SASL or TLS settings as any client and to each Connect REST API over HTTPS with basic authentication where the workers require it.
- Many teams, shared clusters 9 out of 10
- Tenants scope each team to its own topics, consumer groups and connectors on a shared cluster, and RBAC adds Allow, Deny or Stage per action.
On Debezium. Kpow has no separate Debezium integration: Debezium runs as ordinary Kafka Connect connectors, and Kpow manages them through its Kafka Connect configuration and Kafka Connect management pages, which say sensitive config values appear redacted and are not sent in plaintext when a config is edited. The Debezium-specific work is in the release notes: release 81 added creating and editing Debezium connectors, and release 90.1 added topic inference for Debezium connectors and Unreachable connectors. Factor House’s CDC playground project deploys a Debezium PostgreSQL connector through Kpow’s UI.
Where it falls short. Its documentation describes no reading of Debezium’s JMX metrics, such as how far a connector is behind its source, and no editing of a connector’s committed source offsets, which stay a job for the Connect REST API. Kpow governs people working through Kpow, so the Connect REST API stays open to anyone the workers themselves let in. RBAC, masking, staged mutations and the full audit log need Kpow Enterprise; Community Edition is free for 3 clusters and 10 users.
Compare Kpow vs Kafbat UIKpow vs AKHQ
Rank 2 Kafbat UI
72 out of 110 Total
- Cost a year
- $0 licence, about $8,640 in operator time (modelled)
- On Debezium
- Debezium connectors managed like any other connector, free
- Sign-in
- OAuth2, OIDC and LDAP, free
- Out of the data path ×3 weight, this criterion counts 3 times toward the total
- 9 out of 10
- Production access on request ×2 weight, this criterion counts 2 times toward the total
- 4 out of 10
- Audit trail per person ×2 weight, this criterion counts 2 times toward the total
- 6 out of 10
- CDC connector operations ×2 weight, this criterion counts 2 times toward the total
- 6 out of 10
- Directory and Kafka sign-in
- 7 out of 10
- Many teams, shared clusters
- 6 out of 10
Why these scores for Kafbat UI
- Out of the data path 9 out of 10
- It is one stateless container with no database and no proxy, the same pass as Kpow.
- Production access on request 4 out of 10
- RBAC grants actions per resource and a cluster can be set read-only, but there is no approval step, no time-boxed grant, and its masking applies the same way to every viewer.
- Audit trail per person 6 out of 10
- Its audit log names the logged-in user and records reads when the level is set to ALL, but it writes to a topic or the console with no view in the product, so reading the trail is something you build.
- CDC connector operations 6 out of 10
- It shows connector and task status, creates and edits connectors, and restarts a connector or its failed tasks across several Connect clusters with free RBAC, but documents no auto-restart and nothing specific to Debezium.
- Directory and Kafka sign-in 7 out of 10
- It supports OAuth2 and OIDC, including Microsoft Entra ID, and LDAP or Active Directory, and its documentation does not list SAML.
- Many teams, shared clusters 6 out of 10
- Roles scope permissions per resource and list the clusters they apply to, with no tenant view of a team’s own resources.
On Debezium. Kafbat UI lists Connect clusters beside each Kafka cluster, each with a name, an address and optional basic authentication, as its configuration properties show, and its RBAC rules have CONNECT and CONNECTOR resources. Debezium connectors appear there as Connect connectors. The Kafbat UI review covers its RBAC and release history.
Where it falls short. A Debezium connector whose database is down waits for a person to notice and restart it, and there is no way to grant production access for an hour and have it expire or to hold a config change for approval. Its modelled running cost on one cluster is 6 engineer-hours a month, $8,640 a year at $120 an hour.
Rank 3 AKHQ
62 out of 110 Total
- Cost a year
- $0 licence, about $8,640 in operator time (modelled)
- On Debezium
- Debezium connectors listed like any other connector
- Security default
- Disabled until you enable it
- Out of the data path ×3 weight, this criterion counts 3 times toward the total
- 9 out of 10
- Production access on request ×2 weight, this criterion counts 2 times toward the total
- 3 out of 10
- Audit trail per person ×2 weight, this criterion counts 2 times toward the total
- 4 out of 10
- CDC connector operations ×2 weight, this criterion counts 2 times toward the total
- 5 out of 10
- Directory and Kafka sign-in
- 6 out of 10
- Many teams, shared clusters
- 5 out of 10
Why these scores for AKHQ
- Out of the data path 9 out of 10
- It is one stateless container with no database and no proxy, the same pass as Kpow.
- Production access on request 3 out of 10
- Groups bind actions to resources by regex, but there is no approval step or time-boxed grant, masking is global, and without the JWT signing secret the restriction is in the UI only.
- Audit trail per person 4 out of 10
- Audit events are opt-in to a Kafka topic, reads are not recorded, and there is no view for the trail.
- CDC connector operations 5 out of 10
- It lists connector and task status and restarts a connector or a single task, and can produce a record to a signal topic, with no auto-restart and nothing specific to Debezium.
- Directory and Kafka sign-in 6 out of 10
- It supports LDAP, OIDC and header authentication from a proxy, does not list SAML, and ships with security disabled until you enable it.
- Many teams, shared clusters 5 out of 10
- Groups combine resource types with regex patterns on names and clusters, which limits what a role can reach, but there is no tenant view of a team’s own resources.
On Debezium. AKHQ takes a list of Connect clusters under each Kafka connection, each with its own URL and optional basic authentication, per its cluster configuration, and shows connectors, their tasks and their configuration. The AKHQ review covers the rest.
Where it falls short. Security is off until you configure it, the audit trail is an opt-in topic that does not record reads, and a failed Debezium connector stays failed until someone restarts it. Its modelled running cost on one cluster is 6 engineer-hours a month, $8,640 a year at $120 an hour.
Compare Kpow vs AKHQAKHQ review
Rank 4 Lenses
lenses.io
59 out of 110 Total
- Cost a year
- Team is $4,000 for up to 15 users on one cluster, $6,880 with operator time; 25 engineers needs a custom quote (modelled)
- On Debezium
- Connect alert rules built in
- Deployment
- HQ on PostgreSQL plus an agent and database per cluster
- Out of the data path ×3 weight, this criterion counts 3 times toward the total
- 4 out of 10
- Production access on request ×2 weight, this criterion counts 2 times toward the total
- 4 out of 10
- Audit trail per person ×2 weight, this criterion counts 2 times toward the total
- 7 out of 10
- CDC connector operations ×2 weight, this criterion counts 2 times toward the total
- 6 out of 10
- Directory and Kafka sign-in
- 7 out of 10
- Many teams, shared clusters
- 6 out of 10
Why these scores for Lenses
- Out of the data path 4 out of 10
- It runs a central HQ on PostgreSQL plus an agent and an agent database beside every cluster, and HQ has no high-availability option.
- Production access on request 4 out of 10
- Its masking is the strictest view-time model, global with no escape even for admins, but no approval step or time-boxed grant is described.
- Audit trail per person 7 out of 10
- Audit logs can be read in the product, with no need to build a consumer first.
- CDC connector operations 6 out of 10
- It shows task health, metrics and stack traces, restarts a connector or a single task and has Connect-specific alert rules built in, but documents no auto-restart and nothing specific to Debezium.
- Directory and Kafka sign-in 7 out of 10
- SSO spans Okta, Keycloak, OneLogin, Google and Entra ID, with basic authentication only on Community.
- Many teams, shared clusters 6 out of 10
- Roles attach to groups only, never to individuals, and no scoped view per team is described.
On Debezium. Lenses manages several Connect clusters through its agent, with connector and task health, metrics and built-in alert rules for Connect, which applies to Debezium connectors like any other. The Lenses review covers its tiers and deployment.
Where it falls short. A central HQ on PostgreSQL plus an agent and an agent database for every cluster is more to run beside Connect workers and source databases that already need care of their own. The Team licence stops at 15 users on one cluster, so a larger team is on a custom quote.
Compare Kpow vs LensesLenses review
Rank 5 The Connect REST API and Debezium signals
53 out of 110 Total
- Cost a year
- $0 licence, about $11,520 in operator time (modelled)
- On Debezium
- The API every tool on this page calls, plus Debezium's signal channels
- Security default
- HTTP with no authentication until the workers are configured
- Out of the data path ×3 weight, this criterion counts 3 times toward the total
- 10 out of 10
- Production access on request ×2 weight, this criterion counts 2 times toward the total
- 1 out of 10
- Audit trail per person ×2 weight, this criterion counts 2 times toward the total
- 2 out of 10
- CDC connector operations ×2 weight, this criterion counts 2 times toward the total
- 6 out of 10
- Directory and Kafka sign-in
- 3 out of 10
- Many teams, shared clusters
- 2 out of 10
Why these scores for The Connect REST API and Debezium signals
- Out of the data path 10 out of 10
- There is nothing to deploy beyond the Connect workers themselves, which is the only option here that scores 10.
- Production access on request 1 out of 10
- Anyone who can reach a worker’s REST API can create, change or delete any connector, with no approval step, no expiring grant and no masking.
- Audit trail per person 2 out of 10
- The workers’ own logs are the only record, and nothing ties a call to a person in the directory.
- CDC connector operations 6 out of 10
- It has every Connect operation, including restarting only the failed tasks, and Debezium adds signal and notification channels, but nothing watches the state, nothing restarts automatically, and a signal sent from a script leaves no record of who sent it.
- Directory and Kafka sign-in 3 out of 10
- Workers can serve the API over HTTPS with client certificates, and basic authentication comes from a REST extension, but there is no directory sign-in.
- Many teams, shared clusters 2 out of 10
- One URL reaches one Connect cluster with no notion of which team owns which connector.
On Debezium. The Kafka Connect user guide lists the REST endpoints every Debezium deployment on Connect uses: connector and task status, restarts, and config validation. Debezium adds signals that start or stop ad hoc snapshots through a database table, a Kafka topic or JMX, and notifications it can write to a Kafka topic.
Where it falls short. It is a toolkit, not a tool: status has to be polled, failures noticed and restarts scripted for every Connect cluster, and the REST API grants all of it to whoever can reach it unless the workers are secured. Its modelled running cost is 8 engineer-hours a month, $11,520 a year at $120 an hour.
Compare How to diagnose and fix a failed Kafka Connect connector
Rank 6 Debezium UI (archived)
42 out of 110 Total
- Cost a year
- $0 licence, about $8,640 in operator time (modelled)
- Status
- Repository archived on GitHub; documentation still marks it incubating
- Security
- No authentication or authorization in the UI; connects to unauthenticated Connect only
- Out of the data path ×3 weight, this criterion counts 3 times toward the total
- 9 out of 10
- Production access on request ×2 weight, this criterion counts 2 times toward the total
- 1 out of 10
- Audit trail per person ×2 weight, this criterion counts 2 times toward the total
- 1 out of 10
- CDC connector operations ×2 weight, this criterion counts 2 times toward the total
- 4 out of 10
- Directory and Kafka sign-in
- 1 out of 10
- Many teams, shared clusters
- 2 out of 10
Why these scores for Debezium UI (archived)
- Out of the data path 9 out of 10
- It is a Quarkus web application whose backend calls the Kafka Connect REST interface, with no database and no proxy.
- Production access on request 1 out of 10
- Its documentation says there is no authorization or authentication in the UI itself, so anyone who reaches it can create or change connectors.
- Audit trail per person 1 out of 10
- Nothing records who did what through it.
- CDC connector operations 4 out of 10
- Its create wizard is built for Debezium connector types and validates properties as they are entered, and it lists connectors with their status, but the project is archived, with no auto-restart and no topic or data view.
- Directory and Kafka sign-in 1 out of 10
- There is no sign-in, and it connects only to Kafka Connect instances without authentication, so securing it means putting your own proxy in front.
- Many teams, shared clusters 2 out of 10
- One deployment lists the connectors of one or more Connect clusters, with no notion of which team owns which.
On Debezium. The Debezium UI documentation describes a connector list with status and a Create Connector wizard that guides and validates property entries. The debezium-ui repository is archived. Debezium’s newer Debezium Management Platform runs pipelines on Debezium Server rather than Kafka Connect, so it is not scored here.
Where it falls short. With no sign-in, no permissions and no record of changes, it cannot be pointed at production Connect without a proxy in front, and its connector view stops at Connect: no topics, consumer groups or change events. Its modelled running cost on one cluster is 6 engineer-hours a month, $8,640 a year at $120 an hour.
Rank 7 Conduktor
conduktor.io
67 out of 110 Total
- Cost a year
- 25 Console seats at $1,200 is $30,000 plus $2,880 operator time, so $32,880; Gateway Core adds $60,000 and Gateway Protect, which carries encryption and masking, a further $30,000 (modelled)
- On Debezium
- Task-level auto-restart with history, read-only offsets tab
- Deployment
- Console on PostgreSQL 13+; data-level controls through Gateway, a proxy
- Out of the data path ×3 weight, this criterion counts 3 times toward the total
- 3 out of 10
- Production access on request ×2 weight, this criterion counts 2 times toward the total
- 6 out of 10
- Audit trail per person ×2 weight, this criterion counts 2 times toward the total
- 8 out of 10
- CDC connector operations ×2 weight, this criterion counts 2 times toward the total
- 8 out of 10
- Directory and Kafka sign-in
- 7 out of 10
- Many teams, shared clusters
- 7 out of 10
Why these scores for Conduktor
- Out of the data path 3 out of 10
- Console needs PostgreSQL 13 or later, and its encryption, data-level masking and Virtual Clusters only work when client traffic goes through Gateway, a proxy in the data path.
- Production access on request 6 out of 10
- Masking can exempt users or groups, which beats every other tool here on who sees unmasked data, and cross-team access requests are approved by the owning team, but no expiring grant is described and topic creation that passes policy is a direct API call.
- Audit trail per person 8 out of 10
- Console logs produce, consume and admin requests across more than 70 event types with user, IP and timestamp, browsable in the UI and exported as CloudEvents.
- CDC connector operations 8 out of 10
- Its Kafka Connect page describes failed-task auto-restart with a history, connector alerts and an Offsets tab that shows a source connector’s position in the upstream system, read-only with edits through its API once the connector is stopped, but it says nothing specific to Debezium and does not describe redacting secrets in connector configs.
- Directory and Kafka sign-in 7 out of 10
- Its SSO configuration covers LDAP and OIDC, with guides for Okta, Entra ID and Keycloak, and does not describe SAML.
- Many teams, shared clusters 7 out of 10
- Permissions are set per user or group across clusters, but a user in several groups inherits the most permissive grant, and Virtual Clusters for multi-tenancy need Gateway.
On Debezium. Conduktor’s Console manages Connect clusters from its Kafka Connect page: create connectors from the installed plugin classes, switch between form and JSON views, pause, resume, restart or delete connectors, set alerts and enable auto-restart. Its Offsets tab shows the source partition and source offset a source connector has committed, which for Debezium is its position in the database’s log. The Conduktor review covers the rest.
Where it falls short. Console needs PostgreSQL. Conduktor’s data-level controls, such as encryption, masking of the data itself and virtual clusters for multi-tenancy, run in Gateway, a Kafka proxy that client applications connect through, and Debezium connectors are Kafka clients too, so routing them through Gateway puts it in front of every change event. On AWS Marketplace, Conduktor Enterprise lists Console at $1,200 a seat for the first 100 seats, Gateway Core, which carries virtual clusters, at $60,000 a year, and Gateway Protect, the add-on for encryption and masking, at a further $30,000.
Compare Conduktor review
What teams using Debezium need
This page is about Kafka tools for the team that runs Debezium on Kafka Connect, the way the Debezium architecture page says it is most commonly deployed: Debezium source connectors read each database’s transaction log and write change events to Kafka topics through Connect workers. Debezium is not a Kafka platform, so the question here is which tool best sets up, secures and operates those connectors and the topics they write. General connector management is ranked in the best Kafka tools for Apache Kafka Connect, how Debezium relates to the Connect framework is in Debezium vs Kafka Connect, and what change data capture is and when to use it is in the complete guide to Kafka change data capture.
For some teams Debezium is the reason they run Kafka Connect at all. Shopify’s engineering team wrote in Capturing every change from Shopify’s sharded monolith that it had no Kafka Connect uses until CDC and built its Connect expertise as the project went, and that the initial snapshot held a read lock on each table for its duration, which could take hours, so snapshots ran against MySQL read replicas. A Debezium pipeline is therefore an operation on the source database as much as on Kafka, and the failures that matter show up on both sides.
Out of the data path. Debezium connectors are Kafka Connect tasks, and every Connect task is an ordinary Kafka producer or consumer, so a tool whose controls work only when client traffic passes through a proxy puts that proxy in front of every change event. The cost of a stalled pipeline is not only stale topics. On PostgreSQL, the Debezium PostgreSQL connector documentation says replication slots are guaranteed to retain every WAL segment Debezium needs even during a Debezium outage, and tells teams to monitor slots closely to avoid excess disk consumption, so anything in the path that stops the connector writing also keeps write-ahead log on the production database. A management tool needs nothing more than the Connect REST API and a client connection to Kafka. Kpow is one container with no external database, installed in your own environment and out of the data path. Conduktor Console also connects directly, with a PostgreSQL database of its own; Conduktor’s data-level controls, such as encryption, masking of the data itself and virtual clusters, run in Conduktor Gateway, a Kafka proxy that client applications connect through.
Production access on request. A Debezium connector config carries a database user with replication rights and its password. The Apache Kafka improvement proposal KIP-297 states that connector configurations hold plaintext passwords, that Connect stores them in cleartext in its internal topics, and that the REST API exposes them over unsecured connections; its answer is config providers that load secrets from outside the config. A tool on top has to keep that secret out of the screen while still letting a person change the rest of the config, and has to decide who may create, edit, pause or delete a connector. The second privileged action is a signal. With the Kafka channel enabled, the Debezium signalling documentation says a record on the signal topic whose key matches the connector’s topic.prefix and whose value is an execute-snapshot request starts an ad hoc snapshot of the tables it names, so permission to produce to that topic is permission to re-read production tables. Those controls are compared across the field in Kafka RBAC tools.
Audit trail per person. A tool calls the Connect REST API with one credential, so the workers cannot tell the engineers working through it apart, and the record of who changed a Debezium connector’s table list or restarted it has to come from the tool. Signals need the same record: Debezium’s signalling documentation says that, apart from the source channel, signal channels do not retry, and that after sending a signal you should verify that it completed, which is easier when the record shows who sent it and when. Debezium can also write notifications about snapshot progress to a Kafka topic named by notification.sink.topic.name, which a tool that reads topics can show beside the audit trail. The options are compared in Kafka audit logging tools.
Directory and Kafka sign-in. A tool for Debezium holds three connections: to Kafka with whatever SASL or TLS settings the cluster requires, to each Connect cluster’s REST API over HTTPS, often with basic authentication, and to the schema registry that Debezium’s Avro converter writes to. People then sign in through the company directory over SAML, OpenID Connect or LDAP, so a change to a connector that reads a production database is tied to a named person rather than to a shared credential.
Many teams, shared clusters. CDC usually starts with one database and grows to one connector per source database, each with its own topic.prefix and one topic per captured table, on Connect workers shared by every team whose database is captured. Each team needs its own view of its own connectors and change event topics, and permission to touch only those.
CDC connector operations. The common Debezium failure is outside Kafka: the source database is down or refuses the connection, and the connector fails with it. Restarting the task does nothing until the database is back, so the tool has to show the stack trace before anyone restarts, and an automatic restart needs a cap so a database outage does not become a flood of restart calls. Some Debezium topics are not for consumers at all. The Debezium MySQL connector documentation says the database schema history topic is for internal connector use only, that applications must read schema changes from the separate schema change topic instead, and that the history topic must never be partitioned because it has to keep a single global order. Where only a small share of a database’s updates touch the captured tables, or a low-traffic database shares an instance with a busy one, the PostgreSQL connector documentation says WAL can keep growing because the connector has nothing to confirm, and the fix is heartbeat.interval.ms with a heartbeat table added to the publication. A tool that maps each connector to the topics it writes keeps these internal topics apart from the data, and one that decodes Avro through the registry lets an engineer read a change event’s before and after values without writing a consumer.
No tool here leads on every point: Conduktor shows a source connector’s committed offsets, which for Debezium is its position in the database’s log, and restarts only the failed tasks automatically with a restart history; Lenses has built-in Connect alert rules; and Debezium’s own JMX metrics, described on its monitoring page, go deeper on how far a connector is behind its source than the connector status views on this page. Debezium’s own direction for a UI is now the Debezium Management Platform, which its documentation marks as incubating and which maps each pipeline to a Debezium Server instance on Kubernetes with a PostgreSQL database for its conductor service, rather than managing connectors on Kafka Connect; it is a different way to run Debezium, not a tool for the Connect deployment ranked here.
Factor House has published no customer account of running Debezium with Kpow, so this page carries no customer cards. TD Bank’s public talk, Running Kafka at bank scale, shows its Event Streaming Platform team using the Connectors view in Kpow, and the Kafka Connect page covers it.
The thing that everyone uses it for is just finding data in Kafka. Like, put messages into Kafka, don't know what happened to them.
Derek Troy-West, Co-founder and CEO of Factor House
How a team runs Kpow with Debezium
Installing it beside the workers. Kpow runs as one Docker container, a Java JAR or from the Helm charts, in the same network as the Connect workers that run Debezium. It needs no external database, because its snapshots, metrics and audit log live in topics on the Kafka cluster.
Connecting Connect and the registry. Each Connect cluster is added with CONNECT_REST_URL, with CONNECT_AUTH, CONNECT_BASIC_AUTH_USER and CONNECT_BASIC_AUTH_PASS where the workers require basic authentication, SSL settings for an HTTPS endpoint, and CONNECT_RESOURCE_IDS for several Connect clusters on one Kafka cluster (Kafka Connect configuration). The schema registry Debezium’s Avro converter writes to is configured alongside, so change events decode in data inspect.
Creating a Debezium connector. The create form lists the plugins installed on the workers, Debezium’s included, shows each plugin’s documentation beside its fields and displays form errors as the config is entered; the finished connector can be deployed directly or exported as a REST call for a deployment pipeline (Kafka Connect management). Release 81 added creating and editing Debezium connectors and support for config providers, so a config that loads the database password from outside the connector config can be managed in the same form. Factor House’s CDC playground project walks through the whole setup: a Debezium PostgreSQL connector using pgoutput, an initial snapshot, Avro through a schema registry, compacted topics named ecomm.demo.<table>, a heartbeat table updated every 10 seconds so WAL can be cleaned up safely, and the connector deployed from Kpow’s UI; the From batch to real-time CDC with Debezium article covers the same project.
Editing a config without exposing the password. The Kafka Connect management page says all sensitive config values appear redacted and are not sent in plaintext when a config is edited in Kpow, so an engineer can change a Debezium connector’s table include list without seeing the database password.
Triage when the database is down. Release 90.1 added an Unreachable state for connectors that Connect lists but cannot return, with the example of a connector whose database is down: Kpow shows them with the stack trace it receives and allows actions such as a restart. The same release added topic inference for Debezium connectors, so Kpow can show which topics a Debezium connector writes to and how much it produces, and added last activity and data volume to the Connect tables. For a team that uses a coding agent, the kpow-connect-status agent skill answers whether connectors are healthy and why one failed, and the Factor CLI 1.1 release note shows it with a Debezium connector.
Restarting failed connectors automatically. With CONNECT_AUTO_RESTART set to a list of connector names or wildcards, Kpow restarts failed connectors and their failing tasks, checks for failed connectors every minute, waits 10 minutes by default before trying the same connector again and caps automatic restarts at 50 connectors by default, and each automatic restart is written to the audit log as the kpow_system user (Kafka Connect configuration). The window matters for Debezium: a connector whose database is still down will fail again, and the audit entries show how long it was retrying.
Sending a snapshot signal. Where the Kafka signal channel is enabled (the source channel stays enabled too, because Debezium’s documentation says incremental snapshots need it), an execute-snapshot record keyed by the connector’s topic.prefix can be written to the signal topic from data produce, and reading the notification topic in data inspect shows its progress. Writing to topics is the TOPIC_PRODUCE action in Kpow’s authorization actions, so only the people allowed to start a snapshot can produce to the signal topic, and the audit log records who did.
Deciding who may do what. Kpow splits Connect into CONNECT_CREATE, CONNECT_ALTER_STATE (pause, stop, resume and restart), CONNECT_EDIT_CONFIG, CONNECT_DELETE and CONNECT_INSPECT, and RBAC sets Allow, Deny or Stage per action on resources matched by pattern, so the on-call role can restart Debezium connectors without being able to edit their configs. Tenants give each team a view limited to its own connectors and change event topics, a temporary policy grants extra access for a set time, and staged mutations hold a connector deletion or config change until an administrator approves it.
Signing people in and keeping the record. Engineers sign in through SAML, OpenID Connect or LDAP. Kpow exports connector state counts per Connect cluster, including connect_connector_failed_total and connect_connector_task_failed_total, to Prometheus, so a failed Debezium task is a one-line Alertmanager rule, and the audit log records every connector action and every record produced through Kpow with the user from the identity provider; a webhook sends those records to Slack, Microsoft Teams or a SIEM collector.
Kpow live demo
See the Kpow UI before you connect your Debezium connectors
The live Kpow demo runs on two Apache Kafka clusters on Amazon MSK. It shows brokers, topics, consumer groups, schema registries and the __oprtr_audit_log topic where Kpow keeps its audit trail, with no signup. Connecting the Kafka Connect cluster that runs your Debezium connectors is the step to try next.
For platform teams running change data capture with Debezium.
Try the Kpow demoFAQ
What is the best Kafka tool for Debezium?
On this page’s rubric, Kpow, with 99 of 110 points: it creates and edits Debezium connectors with sensitive values redacted, shows unreachable connectors with their stack trace, maps Debezium connectors to their topics, auto-restarts failed connectors with a cap and an audit entry, decodes Avro change events, gates signal records behind per-person permissions, and runs as one container beside the cluster with no external database. Kafbat UI is the highest-scoring free option.
Does Kpow support Debezium?
Yes, as Kafka Connect connectors. Kpow manages Debezium through its Kafka Connect support; release 81 added creating and editing Debezium connectors and release 90.1 added topic inference for them. There is no separate Debezium integration, and Debezium Server, which runs outside Kafka Connect, is not covered.
Is the Debezium UI still maintained?
The debezium-ui repository is archived, and its documentation says it has no authentication or authorization and connects only to Kafka Connect without authentication. Debezium’s newer Debezium Management Platform is incubating and runs pipelines on Debezium Server on Kubernetes rather than on Kafka Connect.
Why is the PostgreSQL disk filling up while Debezium is down?
Debezium reads changes through a replication slot, and the PostgreSQL connector documentation says the slot keeps every WAL segment the connector still needs, even during an outage. Get the connector running again, and where the captured tables change rarely compared with the rest of the database, set heartbeat.interval.ms and add a heartbeat table to the publication so the connector keeps confirming its position.
Can a Kafka UI trigger a Debezium snapshot?
Yes, where the Kafka signal channel is enabled: an execute-snapshot record keyed by the connector’s topic.prefix on the signal topic starts an ad hoc snapshot, and the source channel stays enabled as well because incremental snapshots need it, as the Debezium signalling documentation describes. Any tool that can produce to a topic can send it; a tool with per-person produce permissions and an audit log also controls and records who did.
Is there a free Kafka UI for Debezium?
Kpow Community Edition is free on up to 3 clusters and 10 users. Kafbat UI and AKHQ are open source and both manage Connect clusters, Debezium connectors included. RBAC, masking, staged approvals and the full audit log need Kpow Enterprise. More free options are compared in the best free Kafka UI tools.
How these tools were scored
Five of the six criteria are the ones Factor House scores on every page for teams that share a Kafka cluster, with the same per-tool scores as the Kafka Connect page; the sixth is CDC connector operations. They are listed here in order of weight. Each criterion is scored 0 to 10: 10 where a tool is the only one here doing it or clearly the best, 8 for a clean documented pass, 5 or 6 for partial support or support that needs work the reader must verify, 1 to 4 for a weak or indirect form, and 0 where it is absent. The weights add up to 11, so totals are out of 110.
1. Out of the data path (counts three times). The tool should run in your own environment, reach Kafka as an ordinary client and Connect through its REST API, and keep no data outside your own cluster. Scored lower: tools that need an external database of their own, and tools whose controls work only when application or connector traffic passes through a vendor’s proxy. A self-hosted container with no external database and no proxy scores 9, a tool with a database of its own 6, one with several databases or an agent per cluster 4, and one that needs both a database and a proxy for its controls 3; 10 is kept for an option with nothing to deploy at all, which here is the Connect REST API itself. This criterion is scored the same way on every Factor House page that uses it, and only its weight changes with the reader.
2. Production access on request (counts twice). Whether an engineer can be granted access to production for one task and have it expire, whether a destructive change can be held for a second person’s approval, and whether sensitive fields can be masked from people who do not need them.
3. Audit trail per person (counts twice). Whether the tool records each action, reads included, against the person from the identity provider, and whether that record can be read in the product and sent to the systems that keep it long term.
4. CDC connector operations (counts twice). Whether the tool creates and edits Debezium connectors and keeps their secrets out of view, shows a connector whose source database is unreachable with its stack trace, restarts the right thing and restarts failed connectors automatically with a limit, maps each connector to the topics it writes, decodes change events through the schema registry, and lets a named person send a signal record. Documented Debezium-specific behaviour counts for more than generic Connect support.
5. Directory and Kafka sign-in (counts once). Whether people sign in through SAML, OpenID Connect or LDAP, and whether the tool connects to Kafka with the same SASL or TLS settings as any client and to the Connect REST API over HTTPS with authentication.
6. Many teams, shared clusters (counts once). Whether each team can be given its own view of its own connectors, topics and consumer groups on a shared cluster, and whether one deployment reaches several clusters.
Costs are modelled for one production Kafka cluster with its Connect cluster and 25 engineers at $120 per engineer hour, using the same hours per tool class as Factor House’s other comparison pages. Tools with a licence carry the published price plus 2 hours a month to run. The open-source UIs, the Debezium UI included, carry 6 hours a month, $8,640 a year, to run, secure and keep current, and scripts against the REST API carry 8 hours a month, $11,520. Kpow’s $7,380 uses the published price of $4,500 per cluster with 100 users included. Lenses publishes a Team price of $4,000 a year for up to 15 users on one cluster, so 25 engineers is a custom quote. Conduktor’s Console is $1,200 a seat on AWS Marketplace, and its Gateway Core and Gateway Protect prices are added for the data-level controls; Conduktor prices Gateway per cluster with a 3-cluster minimum, and the listing does not say how many clusters that figure covers. Kpow Community Edition is free for 3 clusters and 10 users, so a 25-engineer team is on Enterprise. For free options compared at any team size, see the best free Kafka UI tools.
The criteria map onto how Debezium works in the figure below.
Every option is scored from 0 to 10 on each criterion, from the evidence and sources this page cites, and the reason for each score is on its card. The criteria are weighted: Out of the data path counts three times, Production access on request counts twice, Audit trail per person counts twice, CDC connector operations counts twice, Directory and Kafka sign-in counts once and Many teams, shared clusters counts once, for a total out of 110. Out of the data path counts three times. Debezium connectors are Kafka Connect tasks, which are ordinary Kafka clients, so a tool whose controls work through a proxy sits in front of every change event, and on PostgreSQL a stalled pipeline keeps write-ahead log on the source database until it resumes. Production access on request, the per-person audit trail and CDC operations count twice: a Debezium config holds a database credential with replication rights, a record on a signal topic can start a snapshot, and a tool that cannot show a connector whose database is unreachable, restart it with a cap and map it to its topics leaves the team on curl. Directory and Kafka sign-in, and shared clusters, count once. This page is published by Factor House, which makes Kpow. Every option is scored on the same rubric and the same sources: Kpow's per-criterion scores are set the same way as every other option's and are not adjusted, and the weights apply to every option alike. Kpow ranks first on its total of 99 out of 110. The other options follow by total. Conduktor is listed last whatever its total; on its total of 67 it would place third.
Related reading
- Debezium vs Kafka Connect
- The complete guide to Kafka change data capture
- From batch to real-time CDC with Debezium
- Best Kafka tools for Apache Kafka Connect
- Best tools to monitor Kafka Connect connectors
- How to diagnose and fix a failed Kafka Connect connector
- Kafka Connect
- How Shopify uses Apache Kafka in production
- Best Kafka management tools for ecommerce companies and marketplaces