Rising Trend of Databases: In-database Machine Learning

Machine learning processes that predict and forecast by learning from data are built and carried out almost entirely outside the database server. Recently, several database vendors have expanded the capabilities of their products beyond those of a standard database and begun to include several machine learning algorithms. While some database vendors integrate the in-database machine learning service directly into the SQL language in the form of stored procedures, some encourage them to use their service or module, and some suggest installing languages such as Python, R, and Java on the server and while others encourage using third-party platforms that offer machine learning services. In-database machine learning services can be free or paid. Within the framework of the in-database machine learning service offered to the user, there are not only algorithms but also data pre-processing, data visualization functions, and model performance evaluation metrics. Although there are database providers that do not yet offer machine learning services in their products, it is predicted that in-database machine learning services will become a standard in the industry soon. In this study, what the most popular database vendors and cloud database providers offer in-database machine learning services to their users and how they offer this service have been investigated.

Keywords: Machine learning, database, deep learning, artificial intelligence, database service

DOI :10.26650/B/SS28ET06.2023.006.09 IUP :10.26650/B/SS28ET06.2023.006.09 Full Text (PDF)

Veri Tabanlarında Yükselen Trend: Veri Tabanı İçi Makine Öğrenmesi

Zeki Özen

Veriden öğrenerek çıkarımda ve tahminde bulunan makine öğrenmesi süreçleri neredeyse tamamen veri tabanı sunucusunun dışında geliştirilmekte ve çalıştırılmaktadır. Son zamanlarda ise çeşitli veri tabanı sağlayıcıları ürünlerini geleneksel veri tabanı olmanın ötesine taşıyarak makine öğrenmesi hizmetini ürünlerinin içinde yerleşik olarak sunmaya başlamıştır. Kimi veri tabanı üreticileri veri tabanı içi makine öğrenmesi hizmetini doğrudan kendi geliştirdikleri fonksiyonlar ile SQL diline entegre ederken, kimisi kendisine ait bir servis veya modülün kullanımını önermekte, kimisi ise sunucu üzerinde Python, R ve Java gibi dillerin kurulmasını önermekte bir kısmı ise üçüncü Veriden öğrenerek çıkarımda ve tahminde bulunan makine öğrenmesi süreçleri neredeyse tamamen veri tabanı sunucusunun dışında geliştirilmekte ve çalıştırılmaktadır. Son zamanlarda ise çeşitli veri tabanı sağlayıcıları ürünlerini geleneksel veri tabanı olmanın ötesine taşıyarak makine öğrenmesi hizmetini ürünlerinin içinde yerleşik olarak sunmaya başlamıştır. Kimi veri tabanı üreticileri veri tabanı içi makine öğrenmesi hizmetini doğrudan kendi geliştirdikleri fonksiyonlar ile SQL diline entegre ederken, kimisi kendisine ait bir servis veya modülün kullanımını önermekte, kimisi ise sunucu üzerinde Python, R ve Java gibi dillerin kurulmasını önermekte bir kısmı ise üçüncü

Keywords: Makine öğrenmesi, veri tabanı, derin öğrenme, yapay zekâ, veri tabanı servisi

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Global Studies on Management Information Systems

CHAPTER

Rising Trend of Databases: In-database Machine Learning

Veri Tabanlarında Yükselen Trend: Veri Tabanı İçi Makine Öğrenmesi

References

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