Achieve disaster recovery for cloud-native PostgreSQL deployments using YugabyteDB in Microsoft Azure. Discover how you can leverage YugabyteDB’s xCluster disaster recovery (DR) feature to maintain high availability and ensure data integrity. Use the active-active single-master configuration to achieve disaster recovery across two regions.
Postgres is increasingly being used for Gen AI workloads, but users have reported scalability and performance issues, data privacy challenges and high availability concerns. Before you choose a scalable, HA, vector database instead, try running distributed PostgreSQL. Read our new blog to discover when and how to use distributed PostgreSQL for Gen AI workloads.
The enhanced YugabyteDB Kubernetes Operator significantly simplifies the deployment, management, and scaling of YugabyteDB in cloud-native environments. Discover how it automates complex operations to enhance reliability and allows developers and operations teams to focus more on development and less on infrastructure management.
In this blog, we examine how to create a fully autonomous AI travel agent, capable of finding listings and managing bookings using LangChain, OpenAI, PostgreSQL and pgvector, with YugabyteDB as the underlying database. Learn how to build your own AI agent backed by PostgreSQL using components available in today’s ecosystem.
Discover why YugabyteDB is moving beyond PostgreSQL 11 and the challenges and solutions involved in upgrading to PostgreSQL 15 (and beyond). Learn how our engineering team is bringing the most popular PostgreSQL features to YugabyteDB, to deliver a reliable, scalable, highly available, and secure distributed SQL database.
Adopting AI to automate release note creation, the software development teams at YugabyteDB have significantly streamlined their processes. By harnessing OpenAI’s GPT-4, they now generate precise, user-friendly documentation from extensive code changes, enhancing both efficiency and readability for end users.
The blog explores how using geographically located duplicate covering indexes in a YugabyteDB database cluster can ensure low-latency reads in multi-region deployments. These indexes allow applications to read data from the same region they are deployed in, optimizing performance and consistency while avoiding stale data. However, this design increases write latency due to the need for cross-region traffic and multiple data copies.
Operating across two data centers can present challenges such as regional outages affecting distributed quorums and potential data loss from asynchronous replication. This blog explores how YugabyteDB addresses these common issues with specialized deployment patterns that ensure high availability and robust disaster recovery across multiple fault domains.
Disaster recovery is streamlined with YugabyteDB 2.21, introducing industry-first native orchestration features to ensure your data stays safe and readily accessible in today’s volatile cloud environments. This update not only simplifies resilience with the native xCluster DR but also supports database modernization and risk reduction through advanced isolation levels and Kubernetes Operator.
PgBench is widely used for testing database performance, but its default ‘TPC-B like’ workload may not accurately represent true performance. To achieve more realistic load testing, users can employ custom SQL scripts within PgBench. In this demonstration, we’ll show how these adjustments work using YugabyteDB.
