Geo-partitioning with YugabyteDB (versus standing up separate PostgreSQL instances per region) is the ideal solution for use cases that require cross-region data access, faster time to market, and easy deployment management.
Read this blog to discover the pitfalls of standing up separate PostgreSQL instances per region and the advantages of using geo-partitioning in YugabyteDB.
Database High Availability has traditionally been achieved through enhanced and automated disaster recovery solutions. Although these measures reduce the impact of failures, they still result in complete downtime for the application during the failover process. In this blog, we compare this approach with cloud-native solutions for high availability, focusing on resiliency built directly into the database.
Developers can now store, index and query vectors in PostgreSQL using pgvector, eliminating the need for a dedicated vector database. This blog deep dives into pgvector, and explains how to store text embeddings as vectors, execute similarity search, choose between indexes, and scale with distributed SQL.
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.
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.
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.
YugabyteDB’s automatic sharding overcomes PostgreSQL’s partition key limitations by allowing date range queries without modifying table partitioning. Thanks to its global secondary indexes, which don’t require a shared sharding key, YugabyteDB enhances performance by distributing rows across multiple servers. Discover the full advantages and see step-by-step instructions in our latest blog post.
Managing large PostgreSQL tables requires partitioning, which can complicate queries. Migrating to YugabyteDB simplifies scaling by automatically sharding and distributing data and minimizing partition reliance. The article includes demos on PostgreSQL’s partitioning limitations and YugabyteDB’s advantages in distributed tables and scalability.
Discover how to scale PostgreSQL for rapid app growth with our infographic that outlines the evolution to a resilient, compliant, globally scalable distributed deployment. Learn about distributed PostgreSQL’s forms, including multi-master asynchronous replication and sharded or shared-nothing setups, along with their advantages and challenges.
In 2024, data management will be significantly impacted by AI advancements, increasing DBaaS adoption, and a shift towards private cloud usage. AI will enhance IT strategies and database performance, while DBaaS offers operational efficiency and private clouds provide cost-effective solutions for steady-state workloads.
