Do you want to transfer your PostgreSQL data using Kafka? Are you finding it challenging to connect Kafka to PostgreSQL? Well, look no further! This article will answer all your queries & relieve you of the stress of finding a truly efficient solution. Follow our easy step-by-step guide to help you master the skill of efficiently transferring your data from PostgreSQL using Kafka.

It will help you take charge in a hassle-free way without compromising efficiency. This article aims at making the data export process as smooth as possible.

Upon a complete walkthrough of the content, you will be able to successfully connect Kafka to PostgreSQL to seamlessly transfer data to the destination of your choice for a fruitful analysis in real-time. It will further help you build a customized ETL pipeline for your organization. Through this article, you will get a deep understanding of the tools and techniques & thus, it will help you hone your skills further.


You will have a much easier time understanding the ways for setting up the Kafka to PostgreSQL Integration if you have gone through the following aspects:

  • Working knowledge of PostgreSQL.
  • Working knowledge of Kafka.
  • PostgreSQL is installed at the host workstation.
  • Kafka is installed at the host workstation.

Introduction to Kafka

Kafka to PostgreSQL - Kafka Logo.
Image Source: Wikimedia

Apache Kafka is an open-source message queue that helps publish & subscribe high volume of messages in a distributed manner. It uses the leader-follower concept, allowing users to replicate messages in a fault-tolerant way and further allows them to segment & store messages in Kafka Topics depending upon the subject. Kafka allows setting up real-time streaming data pipelines & applications to transform the data and stream data from source to target.

Key Features of Kafka:

  • Scalability: Kafka has exceptional scalability and can be scaled easily without downtime.
  • Data Transformation: Kafka offers KStream and KSQL (in the case of Confluent Kafka) for on-the-fly data transformation.
  • Fault-Tolerant: Kafka uses brokers to replicate data and persists the data to make it a fault-tolerant system.
  • Security: Kafka can be combined with various security measures like Kerberos to stream data securely.
  • Performance: Kafka is distributed, partitioned, and has a very high throughput for publishing and subscribing to messages.

Introduction to PostgreSQL

Kafka to PostgreSQL - PostgreSQL Logo.
Image Source: PNGWing

PostgreSQL is a powerful, enterprise-class, open-source relational database management system that uses standard SQL to query the relational data and JSON to query the non-relational data residing in the database. PostgreSQL has excellent support for all of the operating systems. It supports advanced data types and optimization operations, found in commercial databases such as Oracle, SQL Server, etc.

Key features of PostgreSQL:

  • It has extensive support for complex queries.
  • It provides excellent support for geographic objects & hence it can be used for geographic information systems & location-based services.
  • It provides full support for client-server network architecture.
  • Its write-ahead-logging (WAL) feature makes it fault-tolerant.

Reasons to Migrate Data from Kafka to PostgreSQL

Apache Kafka has proven abilities to manage high data volumes, fault tolerance, and durability. Being an object-relational database, PostgreSQL provides more intricate data types and permits objects to inherit properties, but it also makes using PostgreSQL more challenging. One ACID-compliant storage engine powers PostgreSQL.

When integrated, moving data from Kafka to PostgreSQL could solve some of the biggest data problems for businesses. In this article, we have described two methods to achieve this:

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Methods to Set up Kafka to PostgreSQL Integration

This article delves into both the manual and Hevo methods in great detail.
You’ll also learn about the advantages and disadvantages of each strategy, allowing you to choose the ideal method for your needs.
Below are the two methods:

Method 1: Automated Process Using Hevo to Set Up Kafka to PostgreSQL Integration

Hevo, an Automated No-code Data Pipeline helps you to directly set up Kafka to PostgreSQL connection without any manual intervention. Hevo provides a one-stop solution for all Kafka use cases and provides you with real-time ETL facilities. Hevo initializes a connection with Kafka Bootstrap Servers and seamlessly collects the data stored in their Topics & Clusters. Furthermore, Hevo fetches and updates data from Kafka every 5 minutes!

Hevo supports data ingestion replication from PostgreSQL servers via Write Ahead Logs (WALs) set at the logical level. A WAL is a collection of log files that record information about data modifications and data object modifications made on your PostgreSQL server instance. You can entrust us with your data transfer process and enjoy real-time data streaming. This way, you can focus more on Data Analysis, instead of ETL.

Loading data into PostgreSQL using Hevo is easier, reliable, and fast. You move data from Kafka to PostgreSQL in the following two steps without writing any piece of code: 

Step 1: Authenticate the data source and connect your Kafka account as a data source.

Kafka to PostgreSQL - Configure Apache Kafka
Image Source: Hevo Docs

To get more details about Authenticating Kafka with Hevo Data, visit this link.

Step 2: Configure your PostgreSQL account as the destination.

Kafka to PostgreSQL - Configure PostgreSQL
Image Source: Hevo Docs

To get more details about Configuring PostgreSQL with Hevo Data, visit this link.

Here are more reasons to try Hevo:

  • Faster Implementation: A very quick 3-stage process to get your pipeline setup. After that, everything’s automated while you watch data sync to PostgreSQL or any other destination in real time. 
  • Real-time Alerts & Notifications: With Hevo, you are always in the know about your data transfer pipelines. Receive real-time multiple-format notifications across your various devices.
  • Security: Discover peace with end-to-end encryption and compliance with all major security certifications, including HIPAA, GDPR, and SOC-2.
  • In-built Transformations – Format your data on the fly with Hevo’s preload transformations using either the drag-and-drop interface, or our nifty python interface. Generate analysis-ready data in your warehouse using Hevo’s Postload Transformation.
  • Near Real-Time Replication – Get access to near real-time replication for all database sources with log-based replication. For SaaS applications, near real-time replication is subject to API limits.   
  • Auto-Schema Management – Correcting improper schema after the data is loaded into your warehouse is challenging. Hevo automatically maps source schema with the destination warehouse, so you don’t face the pain of schema errors.
  • Transparent Pricing: Say goodbye to complex and hidden pricing models. Hevo’s Transparent Pricing brings complete visibility to your ELT spend. Choose a plan based on your business needs. Stay in control with spend alerts and configurable credit limits for unforeseen spikes in the data flow.
  • 24×7 Customer Support: With Hevo, you get more than just a platform; you get a partner for your pipelines. Discover peace with round-the-clock “Live Chat” within the platform. Moreover, you get 24×7 support even during the 14-day free trial.
  • Wide Range of Connectors: Instantly connect and read data from 150+ sources, including SaaS apps and databases, and precisely control pipeline schedules down to the minute.
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Method 2: Manual process to Set up Kafka to PostgreSQL Integration

Kafka supports connecting with PostgreSQL and numerous other databases with the help of various in-built connectors. These connectors help bring in data from a source of your choice to Kafka and then stream it to the destination of your choice from Kafka Topics. Similarly, many connectors for PostgreSQL help establish a connection with Kafka.

You can set up the Kafka PostgreSQL connection with the Debezium PostgreSQL connector/image using the following steps:

Step 1: Installing Kafka

To connect Kafka to PostgreSQL, you will have to download and install Kafka, either on standalone or distributed mode. You can check out the following links & follow Kafka’s official documentation, that will help you get started with the installation process:

Step 2: Starting the Kafka, PostgreSQL & Debezium Server

Confluent provides users with a diverse set of in-built connectors that act as the data source and sink, and help users transfer their data via Kafka. One such connector/image that lets users connect Kafka with PostgreSQL is the Debezium PostgreSQL Docker Image.

To install the Debezium Docker that supports connecting PostgreSQL with Kafka, go to the official Github project of Debezium Docker and clone the project on your local system.

Kafka to PostgreSQL - Debezium Docker's Github Project.
Image Source: GitHub

Once you have cloned the project, you need to start the Zookeeper services that store the Kafka configuration, Topic configuration, and manage Kafka nodes. You can do this using the following command:

docker run -it --rm --name zookeeper -p 2181:2181 -p 2888:2888 -p 3888:3888 debezium/zookeeper:0.10

Now with the Zookeeper up and running, you need to start the Kafka server. To do this, open a new console and execute the following command in it:

docker run -it --rm --name kafka -p 9092:9092 --link zookeeper:zookeeper debezium/kafka:0.10

Once you’ve enabled Kafka and Zookeeper, you now need to start the PostgreSQL server, that will help you connect Kafka to PostgreSQL. You can do this using the following command:

docker run — name postgres -p 5000:5432 debezium/postgres

Now with the PostgreSQL server up and running, you need to start the Debezium instance. To do this, open a new console and execute the following command in it:

docker run -it — name connect -p 8083:8083 -e GROUP_ID=1 -e CONFIG_STORAGE_TOPIC=my-connect-configs -e OFFSET_STORAGE_TOPIC=my-connect-offsets -e ADVERTISED_HOST_NAME=$(echo $DOCKER_HOST | cut -f3 -d’/’ | cut -f1 -d’:’) — link zookeeper:zookeeper — link postgres:postgres — link kafka:kafka debezium/connect

Once you’ve enabled all three servers, login to PostgreSQL command-line tool using the following command:

psql -h localhost -p 5000 -U postgres

This is how you can enable your Kafka, PostgreSQL, and Debezium instance servers to connect Kafka to PostgreSQL.

Step 3: Creating a Database in PostgreSQL

Once you’ve logged in to PostgreSQL, you now need to create a database. For example, if you want to create a database with the name “emp”, you can use the following command:


With your database now ready, create a table in your database that will store the employee information. You can do this using the following command:

CREATE TABLE employee(emp_id int, emp_name VARCHAR);

You now need to insert data or a few records into the table. To do this, use the Insert Into command as follows:

Inserting values into the Employee Table.

This is how you can create a PostgreSQL database and insert values in it, to set up the Kafka to PostgreSQL connection.

Step 4: Enabling the Kafka to PostgreSQL Connection

Once you’ve set up your PostgreSQL database, you need to enable the Kafka & PostgreSQL connection, which will pull the data from PostgreSQL and push it to the Kafka Topic. To do this, you can create the Kafka connection using the following script:

curl -X POST -H “Accept:application/json” -H “Content-Type:application/json” localhost:8083/connectors/ -d ‘
 “name”: “emp-connector”,
 “config”: {
 “connector.class”: “io.debezium.connector.postgresql.PostgresConnector”,
 “tasks.max”: “1”,
 “database.hostname”: “postgres”,
 “database.port”: “5432”,
 “database.user”: “postgres”,
 “database.password”: “postgres”,
 “database.dbname” : “emp”,
 “”: “dbserver1”,
 “database.whitelist”: “emp”,
 “database.history.kafka.bootstrap.servers”: “kafka:9092”,
 “database.history.kafka.topic”: “schema-changes.emp”

You can now check and verify the connectors using the following line of code:

curl -X GET -H “Accept:application/json” localhost:8083/connectors/emp-connector

To verify if Kafka is correctly pulling data from PostgreSQL or not, you can enable the Kafka Console Consumer using the following command:

Enabling Kafka Consumer Console

The above command will now display your PostgreSQL data on the console. With Kafka now correctly pulling data from PostgreSQL, you can use KSQL/KStream or Spark Streaming to perform ETL on the data.

This is how you can connect Kafka to PostgreSQL using the Debezium PostgreSQL connector.

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This article teaches you how to set up the Kafka PostgreSQL Connection with ease. It provides in-depth knowledge about the concepts behind every step to help you understand and implement them efficiently. The first method, however, can be challenging, especially for a beginner. It involves manual effort and consumes significant engineering bandwidth. If you wish to save your time and effort in loading data from Kafka to PostgreSQL, try Hevo.

Hevo Data provides an Automated No-code Data Pipeline that empowers you to overcome the above-mentioned limitations. Hevo caters to 150+ data sources (including 50+ free sources) and can seamlessly transfer your data from Kafka to PostgreSQL within minutes.

Hevo’s Data Pipeline enriches your data and manages the transfer process in a fully automated and secure manner without having to write any code. It will make your life easier and make data migration hassle-free.

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Tell us about your experience of connecting Kafka to PostgreSQL! Share your thoughts in the comments section below!

Vishal Agrawal
Technical Content Writer, Hevo Data

Vishal Agarwal is a Data Engineer with 10+ years of experience in the data field. He has designed scalable and efficient data solutions, and his expertise lies in AWS, Azure, Spark, GCP, SQL, Python, and other related technologies. By combining his passion for writing and the knowledge he has acquired over the years, he wishes to help data practitioners solve the day-to-day challenges they face in data engineering. In his article, Vishal applies his analytical thinking and problem-solving approaches to untangle the intricacies of data integration and analysis.

No-code Data Pipeline For PostgreSQL