The Distributed SQL Blog

Thoughts on distributed databases, open source and cloud native

Spring Data REST Services Powered By Distributed SQL – A Hands-on Lab

The Spring application development framework is arguably the most popular framework among Java developers. However, given its extensive breadth and depth, it can be difficult to learn for new users. As the name suggests, Spring Boot makes it easy to boot up with the Spring framework. It shortens development time by taking an opinionated view of the framework and the associated third-party libraries.

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Develop IoT Apps with Confluent Kafka, KSQL, Spring Boot & Distributed SQL

In our previous post “5 Reasons Why Apache Kafka Needs a Distributed SQL Database”, we highlighted why Kafka-based data services need a distributed SQL database like YugaByte DB as their highly scalable, long-term persistent data store. In this post, we show how Confluent Kafka, KSQL, Spring Boot and YugaByte DB can be integrated to develop an application for managing Internet-of-Things (IoT) sensor data.

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Distributed SQL on Google Kubernetes Engine (GKE) with YugaByte DB’s Helm Chart

The glory days of the heavy-weight hypervisor are slowly fading away, and in the last few years, containerization of applications and services is the new reality. With containerization, enterprises can prototype, deploy, and meet scale demands more quickly. To systematically and efficiently manage these large-scale deployments, enterprises have bet on technologies like Kubernetes (aka k8s), a powerful container orchestrator, to get the job done.

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How to Achieve High Availability, Low Latency & GDPR Compliance in a Distributed SQL Database

Today’s developers understand that the key requirement to converting and retaining customers is all about delivering fast and responsive experiences, while remaining resilient to failures and compliant with data governance regulations. YugaByte DB is purpose built for geo-distributed applications that require high availability, high performance and regulatory compliance. In this blog, we are going to “look under the hood,” to explore exactly how YugaByte DB distributes data across multiple clouds,

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How to Monitor YugaByte DB with Prometheus on Docker?

Observability is absolutely vital to operating business-critical data infrastructure at scale. This is why observability is not an afterthought in the YugaByte DB architecture. Every layer of YugaByte DB exposes metrics in the Prometheus format at the /prometheus-metrics endpoint. Given that Prometheus is essentially the de-facto standard for build-your-own infrastructure monitoring and alerting, you can get started with monitoring YugaByte DB in almost no time.

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YugaByte Database Engineering Update – Nov 27, 2018

Lots has happened since our last engineering update about 3 months ago. Below are some of the highlights.

PostgreSQL API Updates & PostgresConf Silicon Valley Wrap-Up

We have made a lot of progress on YSQL, the PostgreSQL compatible distributed SQL API for YugaByte DB! You can also read about YSQL architecture which covers how distributed SQL is implemented in YugaByte DB.

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Distributed Backups in Multi-Region YugaByte DB Clusters

Our post Getting Started with Distributed Backups in YugaByte DB details the core architecture powering distributed backups in YugaByte DB. It also highlights a few backup/restore operations in a single region, multi-AZ cluster. In this post, we perform distributed backups in a multi-region YugaByte DB cluster and verify that we achieve performance characteristics similar to those observed in a single region cluster.

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Getting Started with Distributed Backups in YugaByte DB

YugaByte DB is a distributed database with a Google Spanner-inspired strongly consistent replication architecture that is purpose-built for high availability and high performance. This architecture allows administrators to place replicas in independent fault domains, which can be either availability zones or racks in a single region or different regions altogether. These types of multi-AZ or multi-region deployments have the immediate advantage of guaranteeing organizations a higher order of resilience in the event of a zone or region failure.

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Presto on YugaByte DB: Interactive OLAP SQL Queries Made Easy

Presto is a distributed SQL query engine optimized for OLAP queries at interactive speed. It was created by Facebook and open-sourced in 2012. Since then, it has gained widespread adoption and become a tool of choice for interactive analytics. It supports standard ANSI SQL, including complex queries, aggregations, joins, and window functions. It has a connector architecture to query data from many data sources such as SQL and NoSQL databases as well as traditional big data platforms such as Hive/Hadoop.

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