Admiral’s VRM platform enhances audience engagement and streamlines subscriptions while adhering to GDPR and CCPA standards. Learn why they chose YugabyteDB Managed for its high performance and geo-distribution capabilities, ensuring rapid data access and processing.
Learn to build a scalable AI application with Azure OpenAI Service and YugabyteDB. See how to interface with Azure’s GPT and Embeddings models, embedding storage in YugabyteDB and conducting similarity searches in distributed clusters.
A US-based bank revamped its data platform to meet the demands of the digital banking era and the need for real-time customer interactions. Central to their efforts was a unified data platform, capable of handling trillions of reads and writes while ensuring high availability and low latency, catering to diverse query patterns.
This blog highlights six moments that will increase the risk of an ecommerce website crash. Using examples, it illustrates the short- and long-term financial and reputational impact of such crashes, showing how by modernizing the data layer retailers can ensure site resilience, scalability, and consistent high performance and safeguard their share of the growing eCommerce market.
Discover how YugabyteDB gives you the flexibility to set different RF values and server counts for your read replica cluster. Tailor your replica nodes for optimized low-latency reads across multiple regions while maintaining a separate replication factor for high availability.
YugabyteDB offers ways to geo-distribute reads. While read replicas are one method, they require more infrastructure. An alternative is to enable follower reads for low-latency access from the primary cluster.
Distributed SQL offers greater scalability, availability, and geo-distribution of data compared to PostgreSQL, but it is important to understand the differences in behaviors between the two systems in order to make the most of your distributed SQL database.
This blog examines the geo-distributed deployment topologies offered with YugabyteDB that can future-proof your data infrastructure and support your app’s needs.
Every SQL execution in PostgreSQL and therefore in YugabyteDB YSQL takes time to process. A common way to identify how much is time spent on processing is to use the pg_stat_statements view in the database. However, the time visible in pg_stat_statements might differ from the time a database client registers for the execution. Where does this difference come from? Let’s take a look.
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.