Struggling to choose between PostgreSQL and Starcounter? Both products offer unique advantages, making it a tough decision.
PostgreSQL is a Development solution with tags like open-source, objectrelational, reliable, performant, sql-compliant.
It boasts features such as Relational database management system (RDBMS), Open source with liberal license, SQL compliant and extensive SQL support, High performance and reliability, Fully ACID (Atomicity, Consistency, Isolation, Durability) compliant, Multi-version concurrency control (MVCC) architecture, Asynchronous replication and failover, Table inheritance and table partitioning, Procedural languages support and pros including Robust feature set, High performance, Reliable, Free and open source, Cross platform, Strong community support.
On the other hand, Starcounter is a Development product tagged with inmemory, database, web-applications, high-performance.
Its standout features include In-memory database for high performance, ACID transactions, Shared nothing architecture for scalability, Built-in ORM and query language, Real-time data synchronization, JSON support, Microservices architecture, and it shines with pros like Very fast data access and processing, Good scalability, Simplified development with ORM and query language, Flexible and lightweight architecture.
To help you make an informed decision, we've compiled a comprehensive comparison of these two products, delving into their features, pros, cons, pricing, and more. Get ready to explore the nuances that set them apart and determine which one is the perfect fit for your requirements.
PostgreSQL is an open source, object-relational database management system known for its reliability, performance, and SQL compliance. It runs on all major operating systems and has a rich set of features including complex queries, foreign keys, triggers, views, and ACID compliance.
Starcounter is an in-memory database platform for developing high-performance web applications. It uses a shared-nothing architecture to distribute data across server nodes for scalability.