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Category: Distributed SQL

Three Insights Gained as an Intern at DSS Asia 2022

Three Insights Gained as an Intern at DSS Asia 2022

Hey Everybody! It’s Lakshmi, reporting again from the APJ team!

I recently received valuable first-hand experience helping to run one of the team’s flagship events: the second annual Distributed SQL Summit (DSS) Asia!

This event brought together developers, architects, and business leaders from all over Asia and beyond. Vish Phaneendra’s roundup post provides a great recap. It was exciting to reach close to 1,000 unique attendees and watch 20+ different talks from thought leaders,

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DSS Asia 2022: Event Highlights and Key Takeaways

DSS Asia 2022: Event Highlights and Key Takeaways

We held our second annual Distributed SQL Summit (DSS) Asia annual conference on the 30th and 31st of March 2022, following great feedback from our initial event and user demand.

This two-day online conference was packed with fascinating presentations, discussions, and demos from customers, partners, and our own experts.

With 35 engaging sessions to choose from, and more than 40 speakers, the conference served as a hub for advocates, partners, customers,

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Distributed SQL Tips and Tricks – April 26, 2022

Distributed SQL Tips and Tricks – April 26, 2022

Welcome back to our distributed SQL tips and tricks blog! I have the pleasure of recapping distributed SQL questions from around the Internet.

This blog series would not be possible without Dorian Hoxha, Franck Pachot, and Frits Hoogland. We also thank our incredible user community for not being afraid to ask questions.

Do you have questions? Make sure to ask them on our YugabyteDB Slack channel,

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How to Set Up a Scalable and Highly-Available GraphQL API in Minutes

How to Set Up a Scalable and Highly-Available GraphQL API in Minutes

A modern GraphQL API layer for cloud native applications needs to possess two characteristics: horizontal scalability and high availability.

Horizontal scalability adds more machines to your API infrastructure, whereas vertical scalability adds more CPUs, RAM, and other resources to an existing machine that runs the API layer. While vertical scalability works to a certain extent, the horizontally scalable API layer can scale beyond the capacity of a single machine.

When it comes to high availability,

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New Product Names: YugabyteDB Managed and YugabyteDB Anywhere

New Product Names: YugabyteDB Managed and YugabyteDB Anywhere

Today, we are announcing new names for our product offerings that were previously referred to as Yugabyte Platform and Yugabyte Cloud. The features and capabilities of these products aren’t changing. However, we hope the new names better capture their underlying features and benefits.

We realized that our previous product names did not properly communicate our vision for the product nor easily identify what our products do. But don’t worry, both YugabyteDB and our company name,

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Retail Application Migration: Lessons Learned Moving from On-Prem to Cloud Native

Retail Application Migration: Lessons Learned Moving from On-Prem to Cloud Native

Recently, I came across a sample e-commerce application that demonstrates how to use Next.js, GraphQL engine, PostgreSQL, and a few other frameworks to build a modern web application. The application supports basic e-commerce capabilities such as product inventory and order management, recommendation system, and checkout function. This made me curious as to how much effort it would take to complete a retail application migration from an on-premise to cloud native solution. So I decided to try.

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Using Ebean ORM with YugabyteDB

Using Ebean ORM with YugabyteDB

Ebean is a Java-based Object–Relational Mapping (ORM) application. It is more user-friendly and understandable than traditional ORM tools, such as Hibernate. It achieves this by employing a session-less design that eliminates the concepts of detached/attached beans as well as the difficulties related with flushing/clearing.

Even better, Ebean supports YugabyteDB, a 100% open source, distributed SQL database built to accelerate cloud native agility, lower costs, and reduce risks without vendor lock-in.

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Five Benefits to Running a Distributed SQL Database in Kubernetes

Five Benefits to Running a Distributed SQL Database in Kubernetes

A distributed SQL database is a single logical relational database deployed on a cluster of servers. The database automatically replicates and distributes data across multiple servers. These databases are strongly consistent and support consistency across availability and geographic zones in the cloud.

At a minimum, a distributed SQL database has the following characteristics:

  • A SQL API for accessing and manipulating data and objects
  • Automatic distribution of data across nodes in a cluster
  • Automatic replication of data in a strongly consistent manner
  • Support for distributed query execution so clients do not need to know about the underlying distribution of data
  • Support for distributed ACID transactions

But should you run a distributed SQL database in Kubernetes?

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What Every Application Developer Needs to Know About Geo-Distributed Databases

What Every Application Developer Needs to Know About Geo-Distributed Databases

I’ve been working with distributed systems, platforms, and databases for the last seven years. Back in 2015, many architects began using distributed databases to scale beyond the boundaries of a single machine or server. They selected such a database for its horizontal scalability, even if its performance remained comparable to a conventional single-server database.

Now, with the rise of cloud native applications and serverless architecture, distributed databases need to do more than provide horizontal scalability.

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