How to load data from Timely to Kafka

Learn how to use Airbyte to synchronize your Timely data into Kafka within minutes.

Try Airbyte Cloud Manual method (the hard way)

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Building in-house pipelines

Bespoke pipelines are:

Inconsistent and inaccurate data
Laborious and expensive
Brittle and inflexible

Furthermore, you will need to build and maintain Y x Z pipelines with Y sources and Z destinations to cover all your needs.

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Start syncing with Airbyte in 3 easy steps within 10 minutes

Set up a Timely connector in Airbyte

Connect to or one of 400+ pre-built or 10,000+ custom connectors through simple account authentication.

Set up Kafka for your extracted Timely data

Select where you want to import data from your source to. You can also choose other cloud data warehouses, databases, data lakes, vector databases, or any other supported Airbyte destinations.

Configure the Timely to Kafka in Airbyte

This includes selecting the data you want to extract - streams and columns -, the sync frequency, where in the destination you want that data to be loaded.

Try Airbyte Cloud Manual method (the hard way)

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Check out our interactive demo and our how-to videos to learn how you can sync data from any source to any destination.

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Try Airbyte Cloud Manual method (the hard way)

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Quickly get up and running with a 5-minute setup that enables both incremental and full refreshes for databases of any size, seamlessly scaling to handle large data volumes. Our optimized architecture overcomes performance bottlenecks, ensuring efficient data synchronization even as your datasets grow from gigabytes to petabytes.

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Fully Featured & Integrated

Airbyte automates schema evolution for seamless data flow, and utilizes efficient Change Data Capture (CDC) for real-time updates. Select only the columns you need, and leverage our dbt integration for powerful data transformations.

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Tech Lead at Symend

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How to Sync to Manually

Step 1: Understand Timely and Kafka Data Structures

Before you start moving data, familiarize yourself with both Timely and Kafka data structures. Understand how Timely stores data and the format it uses, as well as the data format Kafka expects. This will help you in transforming the data appropriately.

Step 2: Set Up Kafka Environment

Install and configure a Kafka environment. This includes setting up a Kafka broker and a ZooKeeper instance, which Kafka requires for distributed coordination. Ensure that your Kafka server is running and accessible.

Step 3: Extract Data from Timely

Write a custom script or application to extract data from Timely. This script should query the Timely database and retrieve the data you wish to move. You can use the Timely API or directly access the database, depending on your setup and requirements.

Step 4: Transform Data into Kafka-Compatible Format

Once the data is extracted from Timely, transform it into a format compatible with Kafka. Kafka typically uses key-value pairs and can handle various serialization formats like JSON, Avro, or Protobuf. Ensure your data is serialized into one of these formats for smooth ingestion into Kafka.

Step 5: Produce Data to Kafka Topics

Use the Kafka Producer API to send the transformed data to Kafka. Write a producer script in a language of your choice (e.g., Java, Python) to publish the data to the appropriate Kafka topic. Ensure that your producer is configured to connect to your Kafka broker and the topic exists in Kafka.

Step 6: Monitor Data Flow and Kafka Topics

Once data is being sent to Kafka, monitor the data flow and Kafka topics to ensure data is being received correctly. Use Kafka monitoring tools or scripts to keep track of message throughput, latency, and any errors that may arise.

Step 7: Implement Error Handling and Logging

Incorporate robust error handling and logging into your data movement scripts. Log any errors that occur during data extraction, transformation, or production to Kafka. This will help you diagnose and fix issues quickly, ensuring reliable data movement from Timely to Kafka.