Tutorial at SBBD 2020
https://sbbd.org.br/2020/tutorial-3/
29 September 2020, 14h-16h30

Principles of Distributed Database Systems: spotlight on NewSQL
Patrick Valduriez
Inria, University of Montpellier, CNRS, LIRMM, France
LeanXcale, Spain

The first edition of the book Principles of Distributed Database Systems, co-authored with Prof. Tamer Özsu (University of Waterloo) appeared in 1991 when the technology was new and there were not too many products. In the Preface to the first edition, we had quoted Michael Stonebraker who claimed in 1988 that in the following 10 years, centralized DBMSs would be an “antique curiosity” and most organizations would move towards distributed DBMSs. That prediction has certainly proved to be correct, and most systems in use today are either distributed or parallel.

The fourth edition of this classic textbook [Özsu & Valduriez 2020] provides major updates, in particular, new chapters on big data platforms, NoSQL, NewSQL and polystores. In this tutorial, we introduce these major updates, with a focus on NewSQL.

NewSQL is the latest technology in the big data management landscape, enjoying a fast-growing rate in the DBMS and BI markets. NewSQL combines the scalability and availability of NoSQL with the consistency and usability of SQL. By providing online analytics over operational data, NewSQL opens up new opportunities in many application domains where real-time decision is critical. Important use cases are eAdvertisement (such as Google Adwords), IoT, performance monitoring, proximity marketing, risk monitoring, real-time pricing, real-time fraud detection, etc. NewSQL may also simplify data management, by removing the traditional separation between NoSQL and SQL (ingest data fast, query it with SQL), as well as between operational database and data warehouse / data lake (no more ETLs!). However, a hard problem is scaling out transactions in mixed operational and analytical (HTAP) workloads over big data, possibly coming from different data stores (HDFS, SQL, NoSQL). Today, only a few NewSQL systems have solved this problem.

A first in-depth presentation of NewSQL was given in a tutorial at IEEE Big Data 2019 with Prof. Ricardo Jimenez-Peris (CEO and founder at LeanXcale) [Valduriez & Jimenez-Peris 2019]. In this tutorial, we provide a taxonomy of NewSQL systems based on major dimensions including targeted workloads, capabilities and implementation techniques. We illustrate with popular NewSQL systems such as Google Spanner, LeanXcale, CockroachDB, SAP HANA, MemSQL and Splice Machine. In particular, we give a spotlight on some of the more advanced systems. We also compare with major NoSQL and SQL systems, and discuss integration within big data ecosystems and corporate information systems, using polystores. Finally, we discuss the current trends and research directions.

References

[Özsu & Valduriez 2020] Tamer Özsu, Patrick Valduriez. Principles of Distributed Database Systems, 4th Edition, Springer, 2020.

[Valduriez & Jimenez-Peris 2019] Patrick Valduriez, Ricardo Jimenez-Peris. NewSQL : principles, systems and current trends. IEEE Big Data Conference, Los Angeles, December 2019.

**Postponed to June

Zenith seminar: 19 march 2020, 10h30
Campus Saint Priest, BAT5, 01.124

Innovation : startup strategies
Patrick Valduriez
Inria and LIRMM, Univ. Montpellier, France

Technological innovation as driven by startups is hard to formalize (and manage) as the context may be unknown or quickly changing. To be successful, the innovation process involves not only inventions (new methods) but also context, e.g. user behavior, and timing, e.g. market readiness. In this talk, I illustrate various innovation strategies based on startup success stories, in particular LeanXcale, which delivers a new generation HTAP DBMS product. I also give hints to promote innovation within startups.

Séminaire en ligne Franco-Africain du LIRIMA

Inaugural lecture by Esther Pacitti
Graduate Program in Computer Science , CEFET/RJ, Rio de Janeiro
12 August 2019, 10:00– Auditorium 5,  Maracanã campus

Data Processing: an evolutionary and multidisciplinary perspective
E. Pacitti
Inria and LIRMM, Montpellier, France

The inaugural lecture will address the context of the growth of the amount and variety of data (images, audio, matrixes, text, etc.), produced in various areas (social networks, agronomy, botany, medicine and others), which has also increased the technological and research challenges in the processing  of this large volume of data, termed by the term Big Data.

In the lecture, Professor Esther Pacitti will present a vision of the evolution of data processing  methods from relational databases, distributed databases, and big data to data science. It will also expose some specific applications in Agronomy, Botany and Seismology, and share research experiences in France and Brazil.