Hive Transactional Table vs. Non-Transactional Table

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Before we explore the differences between transactional and non-transactional tables, let’s grasp the basic concepts of Hive tables.

Hive Table

In Hive, a table is a structured storage unit that holds data in a tabular format, similar to a traditional database table. These tables are used for organizing and storing data efficiently within the Hadoop Distributed File System (HDFS).

Hive Transactional Table

A Hive transactional table is a type of table that provides support for ACID (Atomicity, Consistency, Isolation, Durability) transactions. ACID transactions ensure data integrity and consistency, making transactional tables suitable for scenarios where data reliability and accuracy are paramount.

Key Features of Hive Transactional Tables

  • ACID Compliance: Transactional tables adhere to ACID properties, ensuring that data modifications (such as INSERT, UPDATE, DELETE) are atomic, consistent, isolated, and durable.
  • Concurrency Control: These tables support multi-user concurrent data access, allowing multiple users to perform transactions simultaneously without compromising data integrity.
  • Delta Files: Transactional tables use delta files to record changes, making it possible to roll back or commit transactions.

Hive Non-Transactional Table

A Hive non-transactional table, as the name suggests, does not support ACID transactions. These tables are often used for scenarios where data consistency and transactional support are not critical.

Key Features of Hive Non-Transactional Tables

  • No ACID Compliance: Non-transactional tables do not provide ACID compliance, so they are not suitable for use cases where transactional integrity is required.
  • Simplified Structure: These tables have a simpler structure compared to transactional tables, which can be beneficial for scenarios where simplicity is preferred over complexity.


Now that we’ve discussed the characteristics of transactional and non-transactional tables, let’s explore when to use each type.

When to Use Hive Transactional Tables

  • Data Consistency: Transactional tables are the preferred choice when data consistency and integrity are critical, such as in financial applications, healthcare, or any scenario where data accuracy is paramount.
  • Multi-User Environments: In situations where multiple users need to perform concurrent data modifications, transactional tables ensure that transactions are handled safely.

When to Use Hive Non-Transactional Tables

  • Simplified Workloads: Non-transactional tables are suitable for simpler workloads or scenarios where the overhead of ACID transactions is not necessary.
  • Read-Only Data: If you have datasets that are primarily read-only, non-transactional tables can be an efficient choice.

Hive important pages to refer

  1. Hive
  2. Hive Interview Questions
  3. Hive Official Page
  4. Spark Examples
  5. PySpark Blogs
  6. Bigdata Blogs
  7. Spark Interview Questions
  8. Spark Official Page
Author: user