In this excerpt from the recent white paper, Migrating From Monolithic to Cloud Native Operational Databases, we look at three of the challenges faced by companies using the current generation of NoSQL databases and why distributed SQL may be a better choice.
This blog explores how to import and export Avro (a row-based storage format file) and Parquet (a columnar storage format file) and how to process the data with a YugabyteDB database using Azure Databricks.
Temenos could not continue to rely on monolithic databases for manufacturing business operations. They needed a high-availability, scale-out transactional database, so they turned to YugabyteDB. They recently announced that the Temenos Banking Cloud is achieving 100,000 business transactions per second. Learn how that performance benchmark was achieved.
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.
Java is the quintessential language runtime for enterprise applications built on monoliths, microservices, and modular architecture patterns. But when it comes to “Enterprise Java,” Spring is the de facto framework of choice.
The Spring ecosystem—with the simplicity of Spring Boot—has grown to provide integration touchpoints to a majority of the Java ecosystem. For starters, it offers a clean abstraction and “glue” code to build cohesive enterprise applications. However,
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The last decade has seen a rise in usage of distributed SQL databases for transactional, cloud native applications. Popular options include Amazon Aurora, Google Spanner, YugabyteDB, and CockroachDB. All of these databases are resilient to failures and achieve high availability. However, they vary dramatically in the set of relational database management system (RDBMS) features they support.
Google Spanner and CockroachDB have chosen to rewrite the SQL engine from scratch. As a result, they do not implement many of the advanced features supported by a traditional RDBMS.
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YugabyteDB just turned 5 years old, and I cannot help but reminisce about our journey in building this database over the last half-decade. I vividly remember the genesis of the YugabyteDB project, which started with Kannan, Mikhail, and myself meeting for lunch at a restaurant to discuss the future of cloud native databases. After iterating on the idea over a number of such discussions,
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At the Distributed SQL Summit 2020, leaders and architects from notable enterprises in the telco industry joined us for a panel to discuss the future of software development, including important trends such as IoT, 5G, Edge, cloud, and their impact on data infrastructure. Our panelists included Puneet Devadiga from Rakuten Mobile, Hale Donertasli from Rakuten Mobile, Kartik Rallapalli from TracFone Wireless, and James Taylor from Comcast; the panel was moderated by Yugabyte’s head of Data Engineering,
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At the Distributed SQL Summit 2020, Ken Owens – Vice President, Cloud Native Engineering, Mastercard, presented the talk, “The Data Divide: An End User’s Cloud Native Journey to Distributed Databases.”
Because Ken has been working at the intersection of technology and financial services for more than 20 years, he brings a unique perspective to how cloud native and distributed systems can transform, what from the outside may appear to be a slow moving industry,
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Editor’s note: This post was originally published on the Rancher blog, and has been cross-posted here and updated as of July 21, 2020 to account for new versions of software available.
Longhorn is cloud native distributed block storage for Kubernetes that is easy to deploy and upgrade, 100 percent open source, and persistent. Longhorn’s built-in incremental snapshot and backup features keep volume data safe, while its intuitive UI makes scheduling backups of persistent volumes easy to manage.
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