When Blackhawk, a leading branded payment provider, migrated from Microsoft SQL Server to PostgreSQL with Mactores, they reduced operational database costs to just 20% of their previous expenses and scaled their platform 3x. That’s not a theoretical benchmark. It’s the kind of result enterprises are achieving right now by moving from licensed databases to open source.
The shift is accelerating. In the
2025 Stack Overflow Developer Survey, PostgreSQL claimed the #1 spot as the most used database with 55.6% of developers, a 15-point gap over MySQL, and the top position in every major category for the third consecutive year. Most enterprises still on Oracle or SQL Server already know open source is the direction. The question holding them back is simple: how do we migrate without breaking what works?
The Business Case for Open Source
The decision to move off Oracle or SQL Server usually starts with cost, but it rarely ends there. The drivers come down to four factors.
- Cost Savings: Oracle and SQL Server Enterprise licensing can run hundreds of thousands of dollars annually (before per-core fees, support contracts, and add-on modules). PostgreSQL eliminates licensing entirely. For most enterprises, that's an immediate 6-figure reduction in annual spend, with savings compounding as workloads scale.
- Vendor Independence: Commercial databases lock you into a single vendor's pricing, roadmap, and support terms. PostgreSQL is supported by multiple providers. If one stops working for you, switching is low-friction. You own the data, not the vendor.
- Flexibility and Ecosystem: PostgreSQL's extension ecosystem goes far beyond what most commercial databases offer natively. PostGIS adds geospatial capabilities. TimescaleDB handles time-series workloads. pgvector enables AI and vector search directly inside the database. Oracle and SQL Server charge significantly for their services through separate add-ons or integrations. As AI workloads grow, this matters more, not less.
- Security Through Transparency: Open-source code is continuously reviewed, audited, and improved by a global community of developers and security researchers. Vulnerabilities are identified and patched faster than in closed, proprietary systems, where you're dependent on a single vendor's security team and disclosure timeline.
The Real Challenges — and How to Solve Them
Migration off Oracle or SQL Server isn't without friction. The technology has matured, the tooling has improved, and the path is well-travelled. However, it doesn’t mean they come without any challenges. It’s worth understanding them before you start.
- Schema and Code Conversion: Oracle PL/SQL and SQL Server T-SQL don’t translate 1:1 to PostgreSQL PL/pgSQL. Agentic AI accelerators like Mactores’ Aedeon DB can auto-convert 90%+ of schema objects, flagging only complex edge cases for human review.
- Operational Expertise: Managed services like Amazon Aurora, Google AlloyDB, or Azure Flexible Server reduce operational burden — handling patching, backups, scaling, failover, and encryption. For more control, self-managed PostgreSQL with Patroni for HA and pgBackRest for backups is a proven path.
- Performance Tuning: Queries optimized for Oracle’s optimizer may need tuning for PostgreSQL’s planner. However, PostgreSQL’s performance has improved dramatically, and managed services like Aurora add distributed storage that often outperforms the original.
- Enterprise Support: Open source doesn’t mean unsupported. AWS, Google, Microsoft, EDB, Crunchy Data, and Percona all offer enterprise-grade PostgreSQL support with SLAs.
Managed vs. Self-Hosted: A Decision Framework
Not every PostgreSQL deployment looks the same. How you run it matters as much as the migration itself. Here are the three paths, what each one means in practice, and who it's built for.
Managed PostgreSQL (Aurora, AlloyDB, Azure Flexible Server)
With a managed service, the cloud provider handles the infrastructure layer. Patching, backups, scaling, failover, and encryption are all handled automatically. Your DBA team interacts with the database, not the infrastructure running it. Aurora, for example, separates compute and storage, allowing the database to scale independently without manual intervention.
Best for: Enterprises that want to minimize operational overhead, need built-in high availability and disaster recovery, and prefer predictable pricing over infrastructure management.
Self-Managed PostgreSQL
Self-managed means running PostgreSQL on your own infrastructure, whether on-premises or on cloud VMs. You control everything from configuration to patching schedule, backup strategy, and high availability setup. Tools like Patroni handle automatic failover, and pgBackRest manages backups, but your team owns the operational responsibility end-to-end.
Best for: Organizations that need maximum control, have specific compliance or data residency requirements, or have deep PostgreSQL expertise in-house.
Hybrid
A hybrid approach splits workloads across both models. Production databases run on managed services for reliability and uptime guarantees. Development, testing, and non-critical workloads run on self-managed infrastructure to keep costs low. This gives you the stability where it matters and the flexibility where it doesn't.
Best for: Enterprises with a mix of workload criticality or those transitioning gradually from self-managed to fully managed over time.
Make the Move with Mactores
Whether you’re migrating from Oracle, SQL Server, or another commercial database, Mactores has the tooling and expertise to get you to open source faster and safer. Our Aedeon DB accelerator handles automated schema conversion, code scanning, and dependency mapping. Our agentic AI pipeline manages data migration, validation, and testing end-to-end.
Ready to cut your database costs by 80%? Book a 30-minute working session with us.