> For the complete documentation index, see [llms.txt](https://docs.warpstream.com/warpstream/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.warpstream.com/warpstream/kafka/manage-connectors.md). # Manage Connectors This page describes the various options for connector products in WarpStream. WarpStream offers a built-in product called "Managed Data Pipelines" that runs embedded inside the Agents. Managed Data Pipelines is built on-top of the [open source library Bento](https://github.com/warpstreamlabs/bento). For more information on what connectors are available, check out the [Bento docs](https://bento.dev/) as well as the [WarpStream Managed Data Pipelines docs](/warpstream/kafka/manage-connectors/bento.md). In addition, since WarpStream is Kafka protocol compatible, any other Kafka-compatible connector framework like open-source [Apache Kafka Connect](https://kafka.apache.org/documentation/) or [Confluent Platform Connectors](https://docs.confluent.io/platform/current/connect/kafka_connectors.html) will work as expected, although keep in mind you'll need to [tune their settings](/warpstream/kafka/configure-kafka-client/tuning-for-performance.md#kafka-connect) to achieve high throughput with WarpStream. Some self-managed Confluent Platform components are licensed for use with Confluent Cloud and verify the broker type before starting. See [Connect Confluent Platform Components Licensed for Confluent Cloud](/warpstream/kafka/manage-connectors/confluent-cloud-components.md) to configure these components for WarpStream. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.warpstream.com/warpstream/kafka/manage-connectors.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.