# Centralized vs. Decentralized: Performance Comparison between BigchainDB and Amazon QLDB
## 7 Discussion and Conclusions
Nevertheless, the nodes do not use the same number of resources. Some use up to half the resources that the other nodes do. The performance indicators of BigchainDB are 0.11% in CPU utilization and almost 550 MB of memory, both at their maximum values. Amazon QLDB manages to keep the memory usage constant during the requests and at a low level. Although the numbers are not significant, as such, particularly if we consider the computation power of today's computers, in some instances BigchainDB uses as much as 4-5 times the memory and 4-5 times the CPU that QLDB uses. Similarly, as far as the reading cases are concerned, QLDB excels in every example, particularly in memory usage, by being almost constant, and having the same values for both the reading and inserting of the data (45-50 MB). In terms of the CPU usage, in all the provided examples, the value oscillates around 0.012%. BigchainDB also uses a low CPU percentage, which is around 0.06% and is more memory intensive than QLDB, at a maximum of 500 MB. In terms of the performance indicators for reading and inserting operations for each technology, the reading values are almost half the inserting values and exactly as they should be. The two parameters we used when conducting the current study--CPU and RAM consumption--were selected due to the straightforwardness of their record and the useful information they provide about the system's performance. Whilst there are other additional qualitative parameters that could be considered, including data security and privacy, or ease of use, in this case the quantitative technical analysis is considered to be the most crucial. In addition, it is straightforward to estimate the processing performance for each scenario based on the analyzed parameters. Nonetheless, we consider that aspects related to security and privacy need to be briefly examined for the two databases analyzed in the current paper. In the case of QLDB, AWS and the user share security responsibilities ([44,45]). AWS is responsible for protecting the infrastructure that runs the selected services, and third-party auditors test and verify its effectiveness on a regular basis as an added layer of security. Generally, it is recommended to set up accounts with AWS IAM (Identity and Access Management) and add extra layers of security such as MFA, SSL/TSL, activity logging via AWS CloudTrail, AWS encryption solutions, and using advanced managed security services for data protection (e.g., Amazon Macie). In the case of the user, responsibility is determined by the services used, as well as factors such as data sensitivity and project requirements. In a decentralized system such as BigchainDB, the security of each node and the aggregate security across the entire network are extrinsic, which means that the security rules governing confidentiality, availability, and integrity exist outside of the core network design. For instance, if all the nodes have weak security rules, the network is vulnerable to breaches. In contrast, even if a small fraction of the network nodes adheres to reasonable security standards, the network as a whole can withstand attacks. To enhance each node's security and privacy regarding the data traffic, all of the stored data needs to be encrypted at rest and in a transparent manner to BigchainDB, MongoDB, and Tendermint, and all data needs to be encrypted in transit and to enforce the use of HTTPS for the HTTP API and Websocket API. This can be achieved by using Nginx. What is noteworthy for the BigchainDB's reading cases is that, for reading operations, the CPU utilization is always at its highest only for the primary node, while for all the other nodes it reaches values close to those registered by QLDB, but still with 4-4.1% more consumption. For inserting data, QLDB does not exceed 50 MB in terms of memory utilization, while BigchainDB's memory utilization has an almost linear growth, being proportional to the number of inserts that are made.