Data Storage Methods

Physical and Logical Data Storage

Physical data storage is about how and where data is saved in the hardware, such as in sectors, tracks, and pages on a disk. Meanwhile, logical data structures are about how data is represented to the user, for example, in tables with columns and rows.

Data storage methods refer to the techniques used to organize, store, and retrieve data on storage devices. They influence how efficiently data can be accessed, written, and managed, especially on hard disks. Understanding the differences between random storage and fixed storage helps in selecting the most suitable method based on specific data and performance requirements. Below is a detailed breakdown:

Data Storage Methods (Not Limited to Relational Database - RDB)

Data storage methods apply across various database types, not just relational databases (RDB). These methods are essential for efficiently storing data in file systems, NoSQL databases, and distributed databases. The two primary methods are random storage and fixed storage:

Random Storage

• Depends on Input Sequence: In random storage, data is stored based on the sequence in which it arrives or according to available space. This means data isn’t stored in a particular order or location, but wherever there is free space on the storage medium.
• Data is Stored at Any Available Space: When data is written, the system finds any open spot in the hard disk and stores the data there. The storage layout becomes scattered, potentially resulting in fragmentation—where related data gets split across different areas of the disk.
• Write Efficiency: Random storage is generally faster for writing operations because data doesn’t need to be placed in any specific location. This flexibility allows the system to write data quickly to any available space without predefining the storage location.
• Read Efficiency: However, reading data is slower because data pieces may be scattered across the disk. The system has to locate each piece, which increases access time. For data retrieval, the system must access multiple parts of the disk, which is slower than accessing data from a contiguous location.

Fixed Storage

• Predefined Location in Hard Disk: In fixed storage, data is stored in specific, predefined locations on the disk, such as designated sectors, magnetic tracks, or cylinders. Each type or block of data has a designated storage area, ensuring that related data remains close together.

• Data is Stored to These Positions: Data is consistently placed in fixed locations, making the layout organized. For instance, a specific record type or range of data is always written to the same sectors or track locations.

• Write Efficiency: Fixed storage is slower for writing because the system has to locate the predefined positions first before data can be written. This lookup step can take additional time and is less flexible than random storage.

• Read Efficiency: Reading data is faster because related data is stored together in predefined locations. This setup reduces the need to search across the disk, thus improving read times. When data is structured and regularly accessed, fixed storage is highly beneficial.

Comparison of Efficiency

The efficiency of these storage methods varies for writing and reading:

• Random Storage:

  • Write Speed: Fast, as data can be stored in any available space.
  • Read Speed: Slow, as data may be scattered, making retrieval time-consuming.

• Fixed Storage:

  • Write Speed: Slow, as the system must first locate predefined positions before storing data.
  • Read Speed: Fast, because data is organized in fixed locations, reducing access times.

Choosing the Better Storage Method – Depends on Requirements

Whether random or fixed storage is better depends on the specific requirements of the system and data characteristics:

• For Small Amounts of Data: There’s generally no need to predefine storage locations, as the data volume is manageable, and retrieval times aren’t significantly affected by random placement.

• For Large Amounts of Data (Big Data): Managing and accessing large volumes of data is more challenging. Fixed storage may offer efficiency advantages, as it allows faster read times, which is crucial for frequently accessed data.

Big Data Challenges in Storage

As data grows into massive volumes, storage and retrieval face unique challenges, especially with hard disks and memory:

• Frequent and Repetitive Reads: In big data, certain data segments are often accessed repeatedly, exacerbating access time issues, especially if data is scattered.

• Solutions to Speed Up Access:

  • Pre-Calculation: Pre-computing operations like SUM and GROUP BY allows data to be retrieved faster for aggregate queries, reducing computational time during retrieval.
  • Fixed Storage for Specific Data: For critical data ranges or frequently accessed data, fixed storage can be beneficial, storing this data in specific, contiguous areas.

Database System Principle – Storage Selection

The principle of data storage in a database system is selecting the best storage method based on data access patterns, size, and performance needs:

Choosing a Storage Method: One must choose between random and fixed storage based on data access frequency and the importance of fast retrieval.

Irreversible Choice: Once data is stored using a specific method, changing the storage method is often difficult without major reorganization. Therefore, understanding data requirements and choosing the appropriate method is essential to long-term performance.

In conclusion, the method you choose for data storage (random or fixed) should align with the expected data volume, access patterns, and the system's performance needs.