Yugabyte is thrilled to announce its newest partnership with AWS, adding the status of AWS Service Ready Partner for PrivateLink to AWS Graviton Ready Partner. The collaboration offers customers in sectors like finance, healthcare, and government more secure, reliable, and cost-effective cloud-native database options.
YugabyteDB is the first distributed SQL database to receive the designation of AWS Graviton Ready Partner. Learn how we tested and optimized our database using Graviton ARM processors, and see how we delivered strong performance numbers.
In this blog, we will explore how YugabyteDB Change Data Capture (CDC) and open table formats like Apache Iceberg can be used to build data lakes in Amazon S3 using a single copy of the data and achieve low data ingestion latency while avoiding costly rewrites to support updates/deletes and schema evolution.
Spring Boot is a popular framework for building cloud native applications. It makes configuring an application easy and helps you off the ground quickly. Each Spring Boot application is stand-alone and self-contained, which makes all of them easy to deploy in a distributed fashion – to containers or on Kubernetes.
YugabyteDB Managed (formerly Yugabyte Cloud) is our database-as-service offering. It is a perfect match for Spring Boot applications, especially ones made highly available with Kubernetes.
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Spring Boot is an extremely popular framework for building cloud native applications. It makes configuring an application easy and offers lots of starters to get you off the ground quickly. Each Spring Boot application is stand-alone and self-contained, which makes them easy to deploy in a distributed fashion – to containers or, even better, on Kubernetes.
YugabyteDB Managed (formerly Yugabyte Cloud) is a perfect match for Spring Boot applications,
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Serverless applications allow developers to run code without having to provision or manage any servers; developers can just concentrate on implementing the business logic of their applications.
As workloads move to the cloud, serverless applications are gaining tremendous popularity with developers. Serverless frameworks allow developers to program for the cloud to take advantage of elastic scaling for workloads and provide cost benefits of using pay-for-use features, only getting billed for compute time they consume.
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YugabyteDB is easy to get started with on the infrastructure of your choice including public cloud platforms, private cloud environments, and any Kubernetes distribution. For example, you can quickly customize and deploy in AWS thanks to CloudFormation templates. AWS CloudFormation is one of the many ways to automate a public cloud deployment in a consistent manner.
Before we dive in, we wanted to let you know that the Yugabyte team has been working from home in order to do our part with social distancing and to help with containment efforts.
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This post addresses a concern raised about a benchmarking result we recently published comparing the performance of YugabyteDB, Amazon Aurora and CockroachDB. It was pointed out that we unfairly used the default isolation level for each database rather than use serializable isolation level in all databases (even though serializable level was not required for these workloads). In addition, we are also happy to share additional results with the workloads run at YugabyteDB’s serializable isolation level.
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Today’s microservices rely on data with different models and read/write access patterns. Polyglot persistence, first introduced in 2008, states that each such data model should be powered by an independent database that is purpose-built for that model. This post highlights the loss of agility that microservices development and operations suffer when adopting polyglot persistence. We review how distributed SQL serves as an alternative approach that doesn’t compromise this agility.
Polyglot Persistence in Action at an E-Commerce App (Source: Martin Fowler)
Breaking down monolithic applications into smaller,
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DynamoDB is AWS’s NoSQL alternative to Cassandra, primarily marketed to mid-sized and large enterprises. It works best for those who require a flexible data model, reliable performance, and the automatic scaling of throughput capacity. In a nutshell, DynamoDB’s monthly cost is dictated by data storage, writes and reads. Let’s walk through a synopsis.
