Related papers: The Redesigned BaBar Event Store: Believe the Hype
Traditional database systems are built around the query-at-a-time model. This approach tries to optimize performance in a best-effort way. Unfortunately, best effort is not good enough for many modern applications. These applications…
Dynamic graph storage systems are essential for real-time applications such as social networks and recommendation, where graph data continuously evolves. However, they face significant challenges in efficiently handling concurrent read and…
Halls of Fame are fascinating constructs. They represent the elite of an often very large amount of entities---persons, companies, products, countries etc. Beyond their practical use as static rankings, changes to them are particularly…
With the current trend in Model-Based Systems Engineering towards Digital Engineering and early Validation & Verification, experiments are increasingly used to estimate system parameters and explore design decisions. Managing such…
The BaBar experiment at SLAC is in its fourth year of running. The data processing system has been continuously evolving to meet the challenges of higher luminosity running and the increasing bulk of data to re-process each year. To meet…
Today's storage systems expose abstractions which are either too low-level (e.g., key-value store, raw-block store) that they require developers to re-invent the wheels, or too high-level (e.g., relational databases, Git) that they lack…
Data replication is essential to ensure reliability, availability and fault-tolerance of massive distributed applications over large scale systems such as the Internet. However, these systems are prone to partitioning, which by Brewer's CAP…
Applications in science and engineering often require huge computational resources for solving problems within a reasonable time frame. Parallel supercomputers provide the computational infrastructure for solving such problems. A…
Big Data systems are increasingly having to be longer lasting, enterprise-wide and interoperable with other (legacy or new) systems. Furthermore many organizations operate in an external environment which dictates change at an unforeseeable…
The volumes and complexity of data that companies need to handle are increasing at an accelerating rate. In order to compete effectively and ensure their commercial sustainability, it is becoming crucial for them to achieve robust…
Consistency properties provided by most key-value stores can be classified into sequential consistency and eventual consistency. The former is easier to program with but suffers from lower performance whereas the latter suffers from…
Persistent memory (PMEM) devices present an opportunity to retain the flexibility of main memory data structures and algorithms, but augment them with reliability and persistence. The challenge in doing this is to combine replication (for…
Providing an appropriate level of accessibility and traceability to data or process elements (so-called Items) in large volumes of data, often Cloud-resident, is an essential requirement in the Big Data era. Enterprise-wide data systems…
Reproducibility should be a cornerstone of scientific research and is a growing concern among the scientific community and the public. Understanding how to design services and tools that support documentation, preservation and sharing is…
Procedural memory enables large language model (LLM) agents to internalize "how-to" knowledge, theoretically reducing redundant trial-and-error. However, existing frameworks predominantly suffer from a "passive accumulation" paradigm,…
We study the performance power of software combining in designing persistent algorithms and data structures. We present Bcomb, a new blocking highly-efficient combining protocol, and built upon it to get PBcomb, a persistent version of it…
We introduce a world vision in which data is endowed with memory. In this data-centric systems paradigm, data items can be enabled to retain all or some of their previous values. We call this ability "remembrance" and posit that it empowers…
In industrial recommendation systems on websites and apps, it is essential to recall and predict top-n results relevant to user interests from a content pool of billions within milliseconds. To cope with continuous data growth and improve…
In the current landscape of big data, the reliability and performance of storage systems are essential to the success of various applications and services. as data volumes continue to grow exponentially, the complexity and scale of the…
Database system architectures are undergoing revolutionary changes. Algorithms and data are being unified by integrating programming languages with the database system. This gives an extensible object-relational system where non-procedural…