Struggling to choose between Microsoft SQL Server and Postgres-XC? Both products offer unique advantages, making it a tough decision.
Microsoft SQL Server is a Business & Commerce solution with tags like database, relational-database, sql, data-warehousing, analytics, machine-learning.
It boasts features such as Relational database management system, Transaction processing, Data warehousing, Analytics, Machine learning, High availability, Disaster recovery, Security, Scalability and pros including Wide platform and OS support (Windows, Linux, containers), Mature and feature-rich, Strong performance and scalability, Built-in high availability and disaster recovery, Powerful analytics and machine learning capabilities, Integrates well with other Microsoft products and Azure cloud.
On the other hand, Postgres-XC is a Databases product tagged with clustering, scalability, high-availability, open-source.
Its standout features include Shared-nothing architecture for horizontal scalability, Automatic query routing and parallelization, Support for distributed transactions, Automatic failover and load balancing, Support for table partitioning across nodes, Support for multi-master and master-standby clusters, and it shines with pros like Scales horizontally to handle large workloads, Provides high availability through redundancy, Good performance through parallel query execution, Open source with community support.
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.
Microsoft SQL Server is a relational database management system developed by Microsoft. It supports transaction processing, data warehousing, analytics and machine learning. SQL Server runs on Windows and Linux.
Postgres-XC is an open source, shared-nothing clustering extension for PostgreSQL. It provides horizontal scalability across multiple nodes for handling large workloads and high availability through automatic failover.