![]() Aurora Limitless offers a simpler syntax than Citus, which requires creating a non-distributed table and calling a procedure to do what was impossible to add to a CREATE TABLE command. While Citus is an extension that can integrate well with PostgreSQL, it comes with certain limitations where no predefined hook can extend the behavior. ![]() However, Aurora Limitless offers more capabilities and is not built on Citus. When coordinators push queries to shards via Foreign Data Wrapper, Citus comes to mind. Its popularity is increasing in the enterprise world.Īurora Limitless is a read-write load-balancing of PostgreSQL. The high interest in this session means that many organizations dealing with Terabytes or Petabytes of data want to use PostgreSQL and need to scale it out. Aurora Serverless scales out only read replicas, and Aurora Limitless goes further with sharding. To avoid disclosing a new feature before the keynote, the session was added to the agenda just a few hours before it was scheduled. It offers the same syntax, protocol, and runtime behavior as the genuine PostgreSQL. Although Amazon Aurora is not PostgreSQL, it uses a fork that users and developers often perceive as PostgreSQL. DAT415 | Convert a Java app and database to PostgreSQL and fix common issues has plenty of examples of rule #1 for migration between databases: instead of mapping features one by one, it's important to understand the business needs and find effective ways to implement them in PostgreSQL.įinally, DAT344-NEW | Achieving scale with Amazon Aurora Limitless Database was a great example of PostgreSQL popularity. Similarity search in SQL databases has become popular but also brings some unusual behavior that users must be aware of, like the result being different when using an index or not.Ĭonversions from other databases, especially Oracle, to PostgreSQL are always a popular topic. However, I was able to attend the excellent live coding session DAT413-R | Using LangChain to build gen AI apps with Amazon Aurora and pgvector: DAT407 | Best practices for querying vector data for gen AI apps in PostgreSQL was also at another hotel. Gen AI is everywhere, and pgvector made embeddings in the database a popular topic. AWS contributed to a few opensource extensions: ![]() Unfortunately, I missed OPN302 | AWS open source strategy and contributions for PostgreSQL, which was at a different hotel than where I spent most of my time. As a Developer Advocate, it helps me to broaden my perspective, learn new things, and understand better how the databases are used. I am interested in knowing why they are passionate about the topics being discussed and what questions they have. I attended some keynotes and sessions at the conference, but their value lay in interacting with other attendees. As I don't often travel to the US, I've also met people not attending the conference but fortunately being around Las Vegas, such as PostgreSQL community contributors and YugabyteDB users. For me, the primary goal of attending a conference is to meet people. Moreover, modifications may be made to optimize database usage in a cloud environment, whether they are minor or extensive.Īs an AWS Hero, this is my second re:Invent that I am attending in person. In this scenario, the security barrier between cloud providers, managed service providers, and database users often necessitates the use of a PostgreSQL fork with added security features, rather than granting full superuser access to the host. While some manage it by installing PostgreSQL on an EC2 instance or a container, others utilize a managed service. Numerous AWS users process their data with PostgreSQL code. Those who consider the database as one infrastructure component, among many others, may not attend PostgreSQL-only conferences, and the presence of the PostgreSQL community at general events becomes crucial. These events include gatherings of CTOs, system architects, developers, data analysts, DevOps engineers, IT managers, and others. ![]() PostgreSQL is a highly popular database that not only appears at events organized by the PostgreSQL community of contributors but also at any event that brings together a community of PostgreSQL users. This month's PGSQL Phriday #014 is about PostgreSQL Events and the publication date coincides with the end of one of the biggest IT conferences, and therefore one of the largest PostgreSQL community gathering, AWS re:Invent, where I've meet a lot of PostgreSQL users and contributors
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