Abstract
There is a growing demand for persistent data in IoT, edge and similar resource-constrained devices. However, standard FLASH memory-based solutions present performance, energy, and reliability limitations in these applications. We propose MRAM persistent memory as an alternative to FLASH based storage. Preliminary experimental results show that its performance, power consumption, and reliability in typical database workloads is competitive for resource-constrained devices. This opens up new opportunities, as well as challenges, for small-scale database systems. MRAM is tested for its raw performance and applicability to key-value and relational database systems on resource-constrained devices. Improvements of as much as three orders of magnitude in write performance for key-value systems were observed in comparison to an alternative NAND FLASH based device. © 2023 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

Abstract
Cloud native database systems provide highly available and scalable services as part of cloud platforms by transparently replicating and partitioning data across automatically managed resources. Some systems, such as Google Spanner, are designed and implemented from scratch. Others, such as Amazon Aurora, derive from traditional database systems for better compatibility but disaggregate storage to cloud services. Unfortunately, because they follow an open-box approach and fork the original code base, they are difficult to implement and maintain. We address this problem with Loom, a replicated and partitioned database system built on top of PostgreSQL that delegates durable storage to a distributed log native to the cloud. Unlike previous disaggregation proposals, Loom is a closed-box approach that uses the original server through existing interfaces to simplify implementation and improve robustness and maintainability. Experimental evaluation achieves 6x higher throughput and 5x lower response time than standard replication and competes with the state of the art in cloud and HPC hardware.

Abstract
While a significant number of databases are deployed in cloud environments, pushing part or all data storage and querying planes closer to their sources (i.e., to the edge) can provide advantages in latency, connectivity, privacy, energy and scalability. This article dissects the advantages provided by databases in edge and fog environments, by surveying application domains and discussing the key drivers for pushing database systems to the edge. At the same time, it also identifies the main challenges faced by developers in this new environment, and analysis the mechanisms employed to deal with them. By providing an overview of the current state of edge and fog databases, this survey provides valuable insights into future research directions.