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14 Top Data Pipeline Key Terms Explained

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 Here are some key terms commonly used in data pipelines 1. Data Sources Definition: Points where data originates (e.g., databases, APIs, files, IoT devices). Examples: Relational databases (PostgreSQL, MySQL), APIs, cloud storage (S3), streaming data (Kafka), and on-premise systems. 2. Data Ingestion Definition: The process of importing or collecting raw data from various sources into a system for processing or storage. Methods: Batch ingestion, real-time/streaming ingestion. 3. Data Transformation Definition: Modifying, cleaning, or enriching data to make it usable for analysis or storage. Examples: Data cleaning (removing duplicates, fixing missing values). Data enrichment (joining with other data sources). ETL (Extract, Transform, Load). ELT (Extract, Load, Transform). 4. Data Storage Definition: Locations where data is stored after ingestion and transformation. Types: Data Lakes: Store raw, unstructured, or semi-structured data (e.g., S3, Azure Data Lake). Data Warehous...
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How to Retain data in Kafka and Get Additional Time for Analysis

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The default topic retention period in Kafka is seven days. However, you can change the current retention period and keep data for a few more days. Hence it provides you additional time for analysis to get business insights.


How to Retain data in Kafka and Get Additional Time for Analysis


Kafka retention period

  • The retention period, you can set on two parameters of bytes and time. Due to cheap storage costs, companies wish to extend the data retention period. 
  • The retention period setup you need in the broker. It is not a deviation that Kafka is designed only for Seven days, and why we need to change it. Since space is cheaper, we can extend the retention period.

Setup for the retention period

Below is the setup in the broker configuration file for the retention period.

log.retention.bytes


  • The most significant size threshold in bytes for deleting a log.


log.retention.ms

  • The length in milliseconds of a log will be maintained before being deleted.


log.retention.minutes

  • Length before deletion in minutes. log.retention.ms is used as well if both are set.


log.retention.hours

  • Length before deletion in hours. log.retention.ms and log.retention.minutes would be used before this value if both are set.

Steps to disable retention period

You can disable the retention period by setting both log.retention.bytes and log.retention.ms to –1. So that we can effectively turn off the data deletion.

Steps to store data outside the broker

If we want our data to stick around for a while, what is the option other than brokers?
  • Move the data outside of Kafka and not retain it internally to the Kafka brokers themselves. 
  • Before data is removed by retention from Kafka, we could store the data in a database, in a Hadoop Distributed File System (HDFS™), or upload our event messages into something like cloud storage.

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