Title: Database Programming - From Active Databases to NoSQL and Cloud
Computing

Abstract: Database applications define highly complex business logic that
cannot be expressed purely in SQL. This prevented them from being moved
completely into the database in order to achieve high performance. Therefore,
vendors of relational databases started eventually to provide procedural
extensions to SQL such as PL/SQL (Oracle Database), SQLPL (IBM DB2), T-SQL
(Microsoft SQL Server), or PL/pgSQL (PostgreSQL). Due to the introduction of
server-side programming languages, databases began to shift from being
absolutely passive to becoming more active. Along with the rapid growth of some
Web companies, radically new approaches to data management, known as NoSQL,
emerged. NoSQL databases broke with not only how data is stored and maintained,
but also how it is accessed and processed. Everyday programming languages such
as Java (e.g., Apache Hadoop), Erlang (e.g., Riak), or JavaScript (e.g.,
MongoDB, CouchDB) were simply used as the query language. While the need for
stronger consistency or SQL stroke back in many cases, the demand for
supporting modern programming languages in databases remained. With the ongoing
transition to cloud computing, developers now want to keep their preferred
programming languages and environments when switching to database-side
programming. Consequently, vendors of cloud databases try to support multiple
popular programming languages such as JavaScript, R, and Python (e.g.,
Microsoft Azure Cosmos DB [NoSQL], Amazon Redshift [SQL]). In this lecture, we
will review the common history of databases and programming languages, give an
introduction into database-side programming for some relevant systems, and
discuss the challenges of effectively and efficiently integrating modern
programming languages with databases.