arch:can_rdbms_scale_under_load

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arch:can_rdbms_scale_under_load [2021/12/19 20:40] – created dakireevarch:can_rdbms_scale_under_load [2026/08/29 07:59] (current) – external edit 127.0.0.1
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-Can RDBMS scale under load? A survey of the case studies+==== Can RDBMS scale under load? A survey of the case studies ====
  
 Relational databases first appeared in 1970 and have been evolving ever since. Nevertheless, can they meet the demands of the new technologies? Can they be used in modern times of distributed high-load computing? Relational databases first appeared in 1970 and have been evolving ever since. Nevertheless, can they meet the demands of the new technologies? Can they be used in modern times of distributed high-load computing?
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 It is important to note that there are two types of scaling: vertical and horizontal [1]. It is important to note that there are two types of scaling: vertical and horizontal [1].
-Vertical scaling, or "scale up", is achieved by increasing the capabilities of one node, for example, by upgrading CPU, adding memory or storage.  This type of scaling does not require code changes but has a limit to its usefulness. +Vertical scaling, or “scale up”, is achieved by increasing the capabilities of one node, for example, by upgrading CPU, adding memory or storage.  This type of scaling does not require code changes but has a limit to its usefulness. 
-Horizontal scaling, or "scale out", is achieved by increasing amount of nodes in the cluster. This type of scaling requires many issues, like resource management, task allocation, and latency. However, this type of scaling has virtually no limit and is how most large-scale applications exist, like social networks.+Horizontal scaling, or “scale out”, is achieved by increasing amount of nodes in the cluster. This type of scaling requires many issues, like resource management, task allocation, and latency. However, this type of scaling has virtually no limit and is how most large-scale applications exist, like social networks.
  
 However, due to their core design originating in 1970, they were not meant for scaling, especially horizontal. There are some solutions, but it is still a common problem. This does not stop them from scaling vertically: better storage, memory, and processors do increase their performance. Even one of the popular RDBMS, MariaDB, only differs from another, more popular RDBMS, MySQL, in the way it stores data. However, due to their core design originating in 1970, they were not meant for scaling, especially horizontal. There are some solutions, but it is still a common problem. This does not stop them from scaling vertically: better storage, memory, and processors do increase their performance. Even one of the popular RDBMS, MariaDB, only differs from another, more popular RDBMS, MySQL, in the way it stores data.
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 To sum up all of the mentioned above, it's clear that traditional RDBMS can't scale enough under a high load. They can scale vertically, but they have their limits and is insufficient for high load computing To sum up all of the mentioned above, it's clear that traditional RDBMS can't scale enough under a high load. They can scale vertically, but they have their limits and is insufficient for high load computing
  
-Literature: +=== References ===
-https://en.wikipedia.org/wiki/Scalability#Horizontal_(scale_out)_and_vertical_scaling_(scale_up) +
-https://en.wikipedia.org/wiki/Relational_database#Market_share +
-Hadjigeorgiou, C. (2013). Rdbms vs nosql: Performance and scaling comparison. MSc in High. +
-Hollingsworth, M. R. (2012). Hadoop and hive as scalable alternatives to RDBMS: A Case Study. +
-Kumar, R., & Charu, S. (2014). Newsql databases: Scalable rdbms for oltp needs to handle big data. International Journal of Modern Computer Science (IJMCS), 3, 13-17.+
  
 +  - [[wp>Scalability#Horizontal_(scale_out)_and_vertical_scaling_(scale_up)|https://en.wikipedia.org/wiki/Scalability#Horizontal_(scale_out)_and_vertical_scaling_(scale_up)]]
 +  - [[wp>Relational_database#Market_share|https://en.wikipedia.org/wiki/Relational_database#Market_share]]
 +  - Hadjigeorgiou, C. (2013). Rdbms vs nosql: Performance and scaling comparison. MSc in High.
 +  - Hollingsworth, M. R. (2012). Hadoop and hive as scalable alternatives to RDBMS: A Case Study.
 +  - Kumar, R., & Charu, S. (2014). Newsql databases: Scalable rdbms for oltp needs to handle big data. International Journal of Modern Computer Science (IJMCS), 3, 13-17.
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