Register now for the Distributed SQL Summit on Nov 12th. This hybrid event gives the distributed SQL community, customers, partners, and industry leaders a forum to explore how they can eliminate complexity and embrace a modern data ecosystem. Join us to discover the latest distributed SQL innovations and use cases, plus the chance to share your experiences (and questions) with peers and industry experts.
Delivering query parallelism is a key step on our journey to narrow the performance gap between Postgres and YugabyteDB. This blog examines the Postgres Parallel Query feature supported and available in the latest version of YugabyteDB. Click to discover how query parallelism is implemented and functions in Postgres, and what we did to ensure the feature works in YugabyteDB.
We are thrilled to announce powerful new capabilities and architectural enhancements — collectively called enhanced Postgres compatibility — that allow a broader range of Postgres apps to run on YugabyteDB. This latest development makes YugabyteDB the perfect database for companies building cloud-native applications and modernizing existing applications to a cloud-native RDBMS. Click to discover what’s new in YugabyteDB and why we decided to build these new capabilities.
We aim to prove YugabyteDB’s enhanced Postgres compatibility by migrating 100 popular open source Postgres applications to YugabyteDB! Discover how you can get involved in the Postgres App Century Challenge.
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.
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.
Need a database that can accommodate a distributed hybrid deployment model, lower read and write latency, and (most importantly) run the existing PostgreSQL application without an expensive rewrite? See how YugabyteDB was able to meet a logistics company’s performance requirements with no PostgreSQL app changes.
A logistics firm sought to enhance the performance and resilience of their RF system. By implementing a hybrid cloud stretch cluster deployment and strategically positioning data close to users, they successfully lowered latency, aligning with user demands for speed and availability. Explore the detailed approach and outcomes in the following analysis.
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.
