Cold vs. Hot Data Storage: What’s the Difference? - DATAVERSITY (2024)

Cold vs. Hot Data Storage: What’s the Difference? - DATAVERSITY (1)

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When it comes to data storage, the temperature must be taken into consideration. The level of layered data storage service, from cold to hot, is described by the temperature setting.

The levels are distinguished according to the level of significance for the business – in other words, how important data is for the business and how often it is accessed. Generally, the terms “cold” and “hot” mean where the data was located earlier (traditional file storage).

Accessed frequently, hot data is kept near the CPUs’ heat and the rotating drives. Cold data – data that is not required often – is kept on tape or a drive farther from the data center floor.

With the moderndigital transformationera, traditional file storage systems are becoming obsolete and are being substituted by the latest software-based file systems. In addition, with the introduction ofthe cloud, things have changed dramatically, and virtual storage mediums are becoming more and more prevalent.

Let us find out the fundamental terms associated with data storage in terms of the current scenario and how to differentiate between them.

Hot Storage

Hot storage is data that requires frequent access instantly. Any piece of information crucial for your business and needs to be retrieved regularly is deemed fit for hot storage.

The data is usually placed in a layered or hybrid storage system to enable fast data access for hot storage.Services catering to hot storageare more likely to do the following:

  • Use driveswith the latesttechnologies
  • Have faster transport protocols
  • Be positioned either near to the client or in multiple regions

Owing to the resource-intensive storage requirements, cloud data storage providers charge a premium for hot data storage. Some popular service providers such as Amazon AWS and Microsoft’s Azure Hot Blobs offer services at hefty amounts.

Layering in Hot Storage

Data stored in the uppermost tier (high priority) should use solid-state drives. These drives are optimized to yield a high rate of transactions and lower latency than traditional hard drives. For other cases, hard disk drives are best suited for situations where access to the drive is heavy, as it showcases higher durability to intensive read and write cycles.

Regardless of the storage medium used, the jobs require instant and consistent response times in hot data storage.

Examples of tasks requiring such type of storage:

  • Interactive video editing
  • Capturing telemetry data
  • Web content
  • Messaging
  • Online transactions
  • Data transformation

Differentiating Cloud Services Based on Hot, Warm, and Cold

Distinguishing the storage type depends on the kind of storage architecture used:

  • For distributed systems using edge devices, hot storage can function as both computational memory and storage for each edge device.
  • Pure cloud services function as cold computational memory and storage where any off-cloud device uses cold storage.

Identifying When to Use Hot Storage

Data required for hot storage includes:

  • Data that transforms at a faster pace
  • Data used for querying customer requests
  • Data used in the latest real-time projects

Since hot storage requires instant and consistent access, cloud services like Google and Amazon have 99.95% accessibility, while Azure has up to 99.99%. Data coming from hot storage is known as “data streams.”

The speed of data transfer mainly depends onseveral routes from which the data passes through to reach from its host to its destination. Data processed nearest to its source will have a higher speed, while data traveling through different networks to reach the developer’s device will have a longer access time.

Cold Storage

Cold storage is used for less frequently accessed data that does not require instant access like hot data. Such data consists of information that is no longer active and is not relevant. Some of the workable examples of data fit for cold storage include:

  • Outdated projects
  • Financial data that needs to be recorded and maintained
  • Data about legal and HR (human resources)
  • Other requirements that need record keeping

The rate of retrieving data and response time for cold storage data systems is slower than services intended for managing active data. Good examples of cold cloud storage are Amazon Glacier and Google Coldline.

Cold data is best kept on storage mediums that provide lower speeds and are more affordable.Tape is one such cold data storage medium. LTO (Linear Tape-Open), developed in the late 1990s, is also another option. To retrieve Linear Tape-Open (LTO) data, the tapes must be physically accessed from storage racks and fixed over a tape reading machine. LTO ranks among the slowest methods of storing data (i.e., coldest medium).

Charges for storing data over cold cloud storage are comparatively less than for warm or hot storage, but a higher per-operation cost is associated with cold storage than other kinds of cloud storage.

What Comes with Cold Data Storage?

Cold data storage is purely offline storage, containing data that is not stored in the cloud. It is ideal for data that is stored on some tangible medium located in a secure environment having no access to the internet. Such data needs to be kept away from the world of the internet (e.g., cryptocurrencies like Bitcoin).

When to Use Cold Storage

Data meant for cold storage – such as legal causes, agreements, or records – stays for quite some time. Since data-versioning is becoming prevalent, old versions of datasets are best suited to be placed in cold storage. This data has not been updated recently but is being queried, also known as “dormant data.”

Retrieving cold storage data takes more time than hot storage. Accessing cold storage data can be done by physically sifting through a set of hard drives and connecting to a computer for retrieving the data.

When to Use Warm Storage

Data that requires continuous access without the restrictions forced by cold storage is fit for warm storage. Warm storage can be in the form of a network-enabled storage drive or a file server at a remote location for a business network.

If you are concerned about overloading the hot storage, files can be stored on warm storage. It will not free up space or resources but protect the data from being lost. Such alternatives are the best option for people in businesses that can keep:

  • Store guides
  • Tutorials
  • Data infrequently accessed, such as documents on a higher-capacity shared drive for employees

AI Is Redefining Data Storage

Data only grows bigger and bigger and, at present, has reached the Zettabyte Age. The future of technology is artificial learning (AI), Deep Learning (DL), ormachine learning (ML), and data is life-blood.

However, when it comes to AI, DL, or ML, data storage can’t be defined as one-size-fits-all. Here, the concept of analytics comes into effect with varied storage requirements depending upon capacity, throughput, latency, IOPS, etc.

The infrastructure that brings out the full potential of AI and ML technology is data growth. And this is precisely why a massive amount of training data is needed to increase the accuracy levels of the predictive environment where the data need to be ingested, stored, and prepared.

However, artificial intelligence (AI) is redefining and revamping the concept of hot and cold data storage. As explained by Alper Ilkbahar, vice president and general manager of data center memory and storage solutions at Intel, “Simply storing images in the cloud is cold, while using AI to recognize faces in images is hot.”

Conclusion

Businesses of all sizes generate a massive volume of data every day. This calls for efficientData Management strategies, especially storage and maintenance. But, first, you need to identify which solution suits your requirements, such as range of expenditure, data needs, and complexity.

Whether you go for hot or cold storage, the most crucial thing to consider is your data usage. If you want quick and easy access, a combination oflocal storage and a cloud providerwill be the right choice for your data.

In the case of long-term storage, a mix of cold storage or a backup provider will be ideal. Such solutions offer reduced storage costs and free up local storage for other data.

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As an expert in data storage and management, I bring a wealth of knowledge and hands-on experience in the field. My expertise is demonstrated through an in-depth understanding of the concepts and technologies associated with modern data storage, including the nuances between hot, warm, and cold storage, as well as the impact of emerging technologies like artificial intelligence (AI) on data storage strategies.

The article by Ashok Sharma explores the critical considerations in data storage, emphasizing the importance of temperature settings and the evolving landscape of storage systems. Let's delve into the key concepts covered in the article:

  1. Temperature-based Data Storage:

    • The article introduces the concept of categorizing data storage into hot and cold based on the frequency of access and significance for the business.
    • Hot storage is for frequently accessed data crucial to the business, while cold storage is for less frequently accessed data.
  2. Traditional vs. Modern Storage Systems:

    • Traditional file storage systems are becoming obsolete, and modern, software-based file systems are replacing them.
    • The cloud has dramatically changed storage paradigms, with virtual storage mediums gaining prevalence.
  3. Hot Storage:

    • Data requiring frequent access is categorized as hot storage.
    • Characteristics of hot storage include the use of the latest drive technologies, fast transport protocols, and proximity to the client or multiple regions.
    • Examples of tasks suitable for hot storage are interactive video editing, telemetry data, web content, and online transactions.
  4. Layering in Hot Storage:

    • The article discusses the importance of layering in hot storage, emphasizing the use of solid-state drives for high-priority data and hard disk drives for other cases.
  5. Differentiating Cloud Services:

    • Storage types (hot, warm, and cold) depend on the storage architecture used, such as distributed systems with edge devices or pure cloud services.
  6. Cold Storage:

    • Cold storage is for less frequently accessed data that doesn't require instant access.
    • Examples of data fit for cold storage include outdated projects, financial data, and legal or HR records.
    • Cold storage is cost-effective but has slower retrieval times compared to hot storage.
  7. When to Use Cold Storage:

    • Cold storage is suitable for data with legal or record-keeping requirements that don't change frequently.
    • Retrieving cold storage data takes more time, and the data is often stored offline.
  8. Warm Storage:

    • Warm storage is for data that requires continuous access without the restrictions of cold storage.
    • It can be in the form of a network-enabled storage drive or a file server at a remote location.
  9. AI and Data Storage:

    • The article touches on the impact of AI, deep learning, and machine learning on data storage.
    • It highlights the need for diverse storage requirements in the AI era, considering factors like capacity, throughput, latency, and IOPS.
  10. Conclusion:

    • The conclusion emphasizes the importance of efficient data management strategies based on specific business requirements.
    • It recommends considering a combination of local storage and cloud providers for quick access or a mix of cold storage and backup providers for long-term storage.

In conclusion, businesses need to align their data storage strategies with their specific needs, taking into account factors such as data usage patterns, cost considerations, and technological advancements. Whether opting for hot or cold storage, the key is to choose a solution that best suits the organization's requirements for efficient data management.

Cold vs. Hot Data Storage: What’s the Difference? - DATAVERSITY (2024)
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