Oracle database Archiving techniques and best practices to handling large data

 💢Oracle database Archiving techniques and best practices to handling large data💢

Alireza Kamrani 

13/10/2024

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Your database is expanding rapidly, how will you manage performance issues effectively using compression, ILM policy, data archiving, partitioning, so on.

Managing database performance during rapid expansion can indeed be challenging, but there are several strategies that can help ensure efficiency and scalability:

1. Compression: Compressing data can significantly reduce storage and SGA requirements and improve I/O performance. This can be particularly useful for large databases where storage costs and performance are critical.

2. Information Lifecycle Management (ILM) Policy: Implementing ILM policies helps manage data throughout its lifecycle, from creation to deletion. By automating data retention and archiving, you can ensure that only relevant data is kept in high-performance storage, while older data is archived. This feature is a common solution for archiving data , save older data into cheaper disk using modifications or access time.

3. Data Archiving: Archiving infrequently accessed data can free up valuable resources and improve performance. Archived data can be stored in less expensive, slower storage, while keeping the active database lean and fast.

4. Partitioning: Partitioning divides a large database into smaller, more manageable pieces. This can improve query performance and make maintenance tasks more efficient. Partitioning can be done based on various criteria, such as range, list, or hash. Also exchange partitions can useful to archiving data. 

5. Indexing: Proper indexing can drastically improve query performance by allowing the database to quickly locate the required data. Regularly reviewing and optimizing indexes is essential for maintaining performance.

6. Query Optimization: Analyzing and optimizing SQL queries can reduce the load on the database and improve response times. This includes rewriting queries, using joins efficiently, and avoiding unnecessary computations.

7. Regular Maintenance: Regular database maintenance, such as updating statistics, rebuilding indexes, and cleaning up unused space, can help maintain optimal performance.

8. Scaling Strategies: Implementing horizontal or vertical scaling strategies can help manage increased loads. Horizontal scaling involves adding more servers, while vertical scaling involves upgrading existing hardware.

9.Using In-Database Archiving: In-Database Archiving enables you to archive rows within a table by marking them as inactive.

These inactive rows are in the database and can be optimized using compression, but are not visible to an application. The data in these rows is available for compliance purposes if needed by setting a session parameter.

With In-Database Archiving you can store more data for a longer period of time within a single database, without compromising application performance. Archived data can be compressed to help improve backup performance, and updates to archived data can be deferred during application upgrades to improve the performance of upgrades.

To manage In-Database Archiving for a table, you must enable ROW ARCHIVAL for the table and manipulate the ORA_ARCHIVE_STATE hidden column of the table. Optionally, you specify either ACTIVE or ALL for the ROW ARCHIVAL VISIBILITY session parameter.

10.Using Oracle Golden Gate: we can use goldengate replication to have source database as a small/lite DB contains the live data and create a second (target) database to saving all data from specific period of time.

By combining these strategies, you can effectively manage performance issues and ensure your database remains efficient and scalable as it grows. 

Regards,

Alireza Kamrani