03 Oct, 2024

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oracle built in compression

5 mins read

Oracle Built-in Compression

As I was working on a recent project; I found myself pondering a question: what’s the best way to compress large datasets in the financial services industry? It’s a common challenge many organizations face; and I’ve seen firsthand the impact it can have on data storage and processing times. In this blog post; I’ll explore the concept of oracle built-in compression and how it can be used to solve this problem; but I’ll also highlight the limitations and potential drawbacks. My goal is to provide actionable insights and encourage readers to reach out to Solix for more information on how to tackle this challenge.

As a computer engineer with a background in AI and machine learning; I’ve had the opportunity to work with various data compression techniques. From my experience; I can attest that finding the right compression algorithm can be a daunting task; especially when dealing with large and complex datasets. Oracle built-in compression is one such technique that has gained popularity in recent years; but I’ll be honest – I’m not a fan of relying solely on built-in compression. In my opinion; it’s essential to consider a more comprehensive approach that takes into account the specific needs of your organization.

So; what is oracle built-in compression; and how does it work? In simple terms; oracle built-in compression is a feature within the Oracle database that allows you to compress data at the block level. This means that the database compresses the data before it’s written to disk; which can lead to significant storage savings. However; as with any compression technique; there are trade-offs to consider. For example; compression can slow down query performance; and decompression can be resource-intensive. In my experience; it’s essential to carefully evaluate the pros and cons of oracle built-in compression before implementing it in your production environment.

Now; let’s consider a real-world scenario where oracle built-in compression might be useful. Imagine a financial institution that needs to store large amounts of customer data; including transactional records and financial statements. By compressing this data using oracle built-in compression; the institution could potentially reduce its storage costs and free up valuable resources for other uses. However; as I mentioned earlier; it’s crucial to consider the potential drawbacks of compression; such as slower query performance and increased decompression times.

So; what’s the solution? In my opinion; a more comprehensive approach would be to use a combination of compression techniques; including oracle built-in compression; along with data deduplication and data archiving. This would allow the institution to store its data in a more efficient manner; while also ensuring that it can be quickly and easily accessed when needed. Solix offers a range of data management solutions that can help organizations like this achieve their goals. For example; our Solix Enterprise Data Management (EDM) platform provides advanced data compression; deduplication; and archiving capabilities that can help reduce storage costs and improve data accessibility.

For example; let’s say the financial institution I mentioned earlier wants to compress its customer data using oracle built-in compression. However; it also wants to ensure that it can quickly and easily access this data when needed. In this case; Solix’s EDM platform could be used to compress the data using oracle built-in compression; and then store it in a deduplicated and archived format. This would allow the institution to reduce its storage costs while also ensuring that it can quickly and easily access its data when needed.

As I mentioned earlier; I’m not a fan of relying solely on oracle built-in compression. Instead; I believe that a more comprehensive approach that takes into account the specific needs of your organization is the key to success. By combining oracle built-in compression with other data management techniques; such as data deduplication and data archiving; organizations can achieve significant storage savings and improve data accessibility. If you’re interested in learning more about how Solix can help you achieve your data management goals; I encourage you to reach out to us at 1.888-GO-SOLIX (1.888.467.6549) or info@solix.

About the Author:

Sandeep is a computer engineer with a background in AI and machine learning. He has extensive experience in the tech industry; having previously worked at leading companies such as Google and Microsoft. Sandeep is a fan of the Florida Panthers and enjoys gaming in his free time. He is passionate about using technology to solve real-world problems and is always looking for new and innovative ways to apply his skills.

Disclaimer:

The opinions expressed in this blog post are those of the author and do not necessarily reflect the views of Solix. The author is not affiliated with Oracle and does not endorse oracle built-in compression. The purpose of this blog post is to provide actionable insights and encourage readers to reach out to Solix for more information on how to tackle data management challenges.