PostgreSQL continues to dominate the database landscape in terms of adoption and popularity. This blog examines why we believe PostgreSQL will continue to be the top database choice for developers, and how YugabyteDB builds on PostgreSQL’s robust capabilities to support modern enterprise environments.
Amazon recently launched Aurora DSQL, a new distributed SQL database that validates the growing importance of distributed SQL and introduces unique architectural features tied to the AWS infrastructure. This blog examines Aurora DSQL’s PostgreSQL compatibility, architectural distinctions, concurrency control, multi-region capabilities, and positioning relative to YugabyteDB in the evolving database landscape.
PostgreSQL is often the database of choice for Ruby on Rails developers, so the simple migration path to YugabyteDB makes it an ideal fit if you want to increase the availability and scalability of your applications. This blog demonstrates how to get up and running with Ruby on Rails backed by PostgreSQL, and how easily you can move your application to YugabyteDB.
YugabyteDB’s introduction of in-place index updates is a significant improvement to PostgreSQL’s traditional index and table update mechanics. This blog examines how YugabyteDB modified the storage layer of PostgreSQL and how this enhancement delivers enhanced performance.
As a distributed cloud-native transactional database with always-on availability and on-demand scaling, YugabyteDB is the ideal fit for containerized applications powered by Kubernetes. We have continued to invest in YugabyteDB on Kubernetes, making great strides and seeing significant customer successes. This blog explores the latest updates.
A key challenge in a distributed SQL database is achieving high throughput and consistency for both write and read operations. This blog explores the new YugabyteDB Cost Based Optimizer (CBO), an essential piece of the puzzle to achieve high throughput for read operations. It highlights the challenges we tackled while developing the CBO, and details how some of the most impactful aspects of YugabyteDB are modeled.
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.
A key part of our effort to achieve full Postgres compatibility is providing support for bitmap scans (a scan type that combines multiple indexes). This blog deep dives into the high-level strategy of bitmap scans and examines how Postgres implements bitmap scans, how we adapted bitmap scans to work for YugabyteDB, and areas where YugabyteDB bitmap scans go beyond vanilla Postgres.
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.
Combine the power of cloud-native distributed database YugabyteDB with real-time, scalable data lake intelligence from watsonx.data. This blog explores how YugabyteDB can be seamlessly integrated with watsonx.data (IBM’s Presto-based data lake) using the Postgres driver, and details critical business use cases.
