In this post, we shine a spotlight on Admiral’s Co-Founder, James Hartig. Read on to learn more about James’ passion for databases and the first time he heard about YugabyteDB. He also discusses his experience using YugabyteDB Managed (formerly Yugabyte Cloud) to serve 10,000 queries per second across three continents.
At the Distributed SQL Summit 2020, James Hartig – Co-Founder at Admiral, presented the talk “How Admiral Scales Globally with YugabyteDB on Google Cloud While Maintaining Single-Digit Latency.”
Admiral’s Go application runs in Google Cloud across 5 regions in 3 continents. This geo-distributed architecture is powered by a single YugabyteDB cluster that delivers an average global read latency of 3ms! In this talk,
Data migration can be a complex and time-consuming task, but proper planning can help streamline the process. In this blog, we’ll demonstrate how to migrate a Sakila demo database from MongoDB to a YugabyteDB cluster using Studio 3T, highlighting the key steps and considerations involved in the process.
YugabyteDB 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 YugabyteDB distributes data across multiple clouds, regions and availability zones.
The SQL vs. NoSQL database split emerged in 2006-2007, but NoSQL’s compromises led developers to continue using SQL/RDBMS for critical workloads. However, recent changes in the NoSQL world have seen the adoption of ACID transactions, which were previously absent, and this post aims to inform architects of these changes and why they are happening now.
MongoDB’s “schemaless” JSON data modeling was initially attractive to web app developers looking to escape the constraints of traditional relational databases, but issues with data durability and ACID transactions have been a consistent challenge. While the recent MongoDB 4.0 release includes multi-document transaction support, this post explores where the platform falls short for transactional, high performance apps.
Welcome to another post in our ongoing series that highlights new features from the latest 1.1 release announced last week. Today we are going to look at document data modeling using the native JSON data type available in YugabyteDB’s Cassandra compatible YCQL API. Note that this data type is specific to YugabyteDB and is not part of the standard Cassandra Query Language (CQL).
With YugabyteDB’s native JSON support,