When many sessions try to insert into the same B-tree leaf page, classic exclusive page locking serializes progress and wastes time on sleep/wake cycles. We’re introducing a batch page insertion path that lets the session holding the page lock insert for itself and its neighbors. The result: dramatically reduced lock waits, and big gains at high client counts (2X throughput boost starting from 64 clients in our benchmark).| OrioleDB Blog
When you optimize the CPU time of a transactional database management system, it comes down to one question an even faster read path, with no manual tuning required.| OrioleDB Blog
Since our last public update, OrioleDB has continued to evolve with a series of new releases. These updates refine the core engine, extend functionality, and improve performance across a range of workloads. Together, they move us closer to a beta release and lay the groundwork for broader adoption.| OrioleDB Blog
In a recent Hacker News discussion, there was some confusion about the differences between OrioleDB and Neon. Both look alike at first glance. Both promise a "next‑gen Postgres". Both have support for cloud‑native storage.| OrioleDB Blog
Since version beta10 OrioleDB supports building indexes other than B-tree. Bridged indexes are meant to support these indexes on OrioleDB tables.| OrioleDB Blog
For a long time now, PostgreSQL has had an extensible Index Access Method API (called AM), which has stood the test of time and enabled numerous robust extensions to provide their own index types. For example: rum, pgvector, bloom, zombodb and others. PostgreSQL 12 introduced the Table AM API, promising equivalent flexibility for table access methods.| OrioleDB Blog
OrioleDB is a storage extension for PostgreSQL which uses PostgreSQL's pluggable storage system. Designed as a drop-in replacement for PostgreSQL's existing Heap storage, OrioleDB aims to overcome scalability bottlenecks and fully utilize modern hardware capabilities. By integrating seamlessly with PostgreSQL, it offers improved performance, efficiency, and scalability without sacrificing the robustness and reliability that PostgreSQL is known for.| OrioleDB Blog
PostgreSQL, a powerful open-source object-relational database system, has been lauded for its robustness, functionality, and flexibility. However, it is not without its challenges – one of which is the notorious VACUUM process. However, the dawn of a new era is upon us with OrioleDB, a novel engine designed for PostgreSQL that promises to eliminate the need for the resource-consuming VACUUM.| OrioleDB Blog
Long story short, OrioleDB alpha version was released more than year ago. More than 200 bugs were fixed since then. Now, OrioleDB reached beta stage. That means we recommend OrioleDB for pre-production testing. The most interesting workloads for testing could include: high transaction throughput, high volume of updates, high volume of in-memory operations, lock bottlenecks and other extreme cases.| OrioleDB Blog
When Hell Freezes Over?| OrioleDB Blog
Traditional database engines were designed in the '80s and early '90s. At that time CPUs were much slower than they are today. Even worse was storage, hard drive head positioning time was enormous. And CPU (or, at most, a few single-core CPUs) was assumed to be infinitely fast in comparison to IOPS. Therefore, systems were designed to save IOPS as much as possible, while CPU overhead was considered a secondary optimization target.| OrioleDB Blog