Database Assignment: In-Memory Databases, Use Cases, and Developments

This report provides a comprehensive overview of in-memory databases. It begins by defining in-memory databases and explaining their core function of storing data in computer's main memory for swift access, contrasting them with traditional relational databases that rely on hard drives. The report explores the advantages of in-memory databases, such as faster data retrieval and processing, making them suitable for scenarios demanding quick access to data. It also highlights the disadvantages, including the temporary nature of main memory and the risk of data loss in case of failure, along with the solutions like snapshot files and replication. The report further discusses the use of in-memory databases in big data applications and the recent technological developments that support their effective implementation. Finally, the report concludes by emphasizing the benefits of using in-memory databases, despite the challenges, and the importance of employing effective preventive measures.

IN MEMORY DATABASES
As the name suggests, the in-memory database is focused on storing data on the computer's
main memory and performing various operations (Wang, Qian, & Chen,2014). This employs a
different strategy as compared to the relational database that is stored in the computer HDD or
SSD hard drive. Use case scenarios that employ the use of these databases include data that need
to be accessed swiftly. The in-memory databases eliminate the need to search through the hard
drive thus facilitating data while eliminating the response time.
The in-memory databases work by differentiating between the column-based and row
bases data. Some in-memory databases can employ either one or both of the arrangements. The
data is stored in the form of identical values and this helps the system to minimize the
transmission time and speed (Kocberber, Grot, Picorel, Falsafi, Lim, & Ranganathan, 2013). The
columnar tabulation helps the computer its resources in computing only the required information
in a single column. The use of in-memory technology was introduced long along but the
computer architecture was not supportive. Recent developments in technology such as data
warehousing, multi-core and 64-bit technology are available.
There are various properties make it possible to use in-memory databases. The database is stored
in the data warehouse where data is collected, cleaned, compressed and organized in a form that
allows easy access and performance of operations (Kimball & Ross, 2011). The 64-bit
architecture ensures that the memory size can be increased up to terabytes. For the operations to
be run effectively, the multi-core processor ensures a higher data performance.
Over the years, there have been recent developments in the use of in-memory databases.
This more so applies to companies that have deployed the use of big data in running their
operations. There is a vast volume of information generated for every unit if time, this data is
used as big data to run most of the developing firm's operations. To ensure efficiency and
effectiveness, the use of in-memory databases reduces the time complexity.

Cons of using in-memory databases
The major disadvantage of using an in-memory database is that the main memory is a
temporary storage of information, in the case of a failure, all the data is lost(Pagano & Pagano,
2011). Nonetheless, there are various technologies used to counter this include snapshot files,
transaction protocol securing, replication and non-violent RAM. The other disadvantage is the
fact that it is difficult to merge multiple main memory. Nonetheless, grid computer uses
specialized software to link various computers' main memory. The link allows the grid computer
to identify and make use of the available main memory, thus creating a vast virtual high-
performance computer with high efficiency.
Summary
From the above report, it is evident that numerous advantages come with using in-
memory databases over relational databases. This is because it brings high speeds resulting from
using the RAM. In addition to the speed, the in-memory database creates an evolution on
manipulating structured and unstructured data across any system. Despite the significant
challenges that come with the use of in-memory databases, employing better prevention
techniques helps a company or an individual to realize their requirements.

ERD

References
Kimball, R., & Ross, M. (2011). The data warehouse toolkit: the complete guide to dimensional
modeling. John Wiley & Sons.
Kocberber, O., Grot, B., Picorel, J., Falsafi, B., Lim, K., & Ranganathan, P. (2013, December).
Meet the walkers accelerating index traversals for in-memory databases. In 2013
46th Annual IEEE/ACM International Symposium on Microarchitecture
(MICRO) (pp. 468-479). IEEE.
Pagano, F., & Pagano, D. (2011, September). Using in-memory encrypted databases on the
cloud. In 2011 1st International Workshop on Securing Services on the Cloud
(IWSSC) (pp. 30-37). IEEE.
Wang, Z., Qian, H., Li, J., & Chen, H. (2014, April). Using restricted transactional memory to
build a scalable in-memory database. In Proceedings of the Ninth European
Conference on Computer Systems (pp. 1-15).