Today, more than 300 companies are relying on TiDB in production to meet their OLTP/OLAP, database scalability, real-time analytics, and unified storage needs.

There’s no denying that analytic (i.e. OLAP) and transactional (i.e. OLTP) workloads put different demands on the underlying database. They have different I/O patterns, different latency expectations, ...

At their annual Scylla Summit conference, ScyllaDB released version 3.0 of their flagship product, ScyllaDB Open Source 3.0. New features include: concurrent OLTP and OLAP; materialized views ...

Google has updated its managed database service — Spanner — with a new columnar engine to help enterprises run complex analytical queries on real-time transactional data for better decision ...

Excerpt from Microsoft SQL Server 2008 Analysis Services Unleashed by Irina Gorbach, Alexander Berger, Edward Melomed Chapter 1: Introduction to OLAP and Its Role in Business Intelligence ...

Despite the widespread use of PostgreSQL by app developers to manage transactional data, its use in analytic apps has been quite limited.

Modern systems are increasingly hybrid, integrating both transactional (OLTP) and analytical (OLAP) workloads in a single architecture.

For example, ETL and reverse ETL, data quality and observability, OLTP and OLAP (aka HTAP), data catalogs fold under data governance platforms, and MLOps fold under AI platforms.