Skip to main content

Don't Fall Into These 5 PostgreSQL Traps

Bennie Grant
Percona

PostgreSQL promises greater flexibility, performance, and cost savings compared to proprietary alternatives. But successfully deploying it isn't always straightforward, and there are some hidden traps along the way that even seasoned IT leaders can stumble into.

In this blog, I'll highlight five of the most common pitfalls with PostgreSQL deployment and offer guidance on how to avoid them, along with the best path forward.

1. Mistaking proprietary forks for true open source, leading to costly vendor lock-in

Because PostgreSQL has become such a trusted open source database platform, some vendors trade on its name while quietly steering customers toward their own proprietary forks. They may advertise themselves as open source, but behind the scenes, they add exclusive extensions, altered code, or management layers.

The best path forward

When evaluating providers, scrutinize claims of "100% compatibility" and verify their releases stay aligned with the PostgreSQL Global Development Group. Be cautious of distributions that depend on closed extensions.

It's also worth asking how much the vendor gives back to the PostgreSQL community. Companies that mostly consume without giving back often rely on selling proprietary add-ons.

2. Underestimating the importance of tailored high availability and disaster recovery strategies

Commercial database vendors often present their high availability and disaster recovery tools as plug-and-play, suggesting everything will run automatically. In reality, those promises of "enterprise-grade uptime" and "built-in resilience" rarely come with clear definitions, and the simplified interfaces or automated failover they showcase usually depend on rigid architectures that don't adapt to the unique needs of your business.

The real shortcomings emerge in moments of crisis. Hardware failures, network outages, or data corruption quickly expose how inflexible these systems really are. Instead of seamless continuity, you may face long outages, lost information, and frustrated customers. And to make matters worse, the fine print of SLAs might exclude exactly the kinds of scenarios you expected to be protected against.

The best path forward

A more resilient approach is to rely on open source high availability frameworks such as  Patroni, which can be adapted to fit the unique demands of your organization. For backup and recovery, community-tested tools such as pgBackRest provide incremental and verifiable protection without the opacity of proprietary "black box" systems.

It's equally important to run failover drills regularly under realistic workloads. While some commercial vendors downplay or even discourage this practice due to the limitations of their own architectures, testing in real conditions is the only way to ensure your DR plan will hold up when it matters most.

3. Paying extra for security features PostgreSQL provides natively

Proprietary database vendors sometimes exploit outdated beliefs about open source security, strategically framing their expensive security bundles as the only safe choices for meeting strict compliance rules.

The reality is that when set up properly, PostgreSQL already delivers strong protections on par with, and sometimes exceeding, those found in commercial databases. These include built-in features such as SSL/TLS encryption for data in transit, role-based permissions, and audit logging. Marketing spin often hides this fact, leaving teams unaware that many of the features they're paying for are already available at no extra cost.

The best path forward

Pairing PostgreSQL's built-in security capabilities with guidance from PostgreSQL specialists ensures that your system is configured to meet regulatory standards without depending on costly proprietary layers. Requesting a side-by-side comparison between a vendor's security bundles and PostgreSQL's native features also makes the price gap clear.

4. Applying incompatible legacy database designs that hamper PostgreSQL's potential

For teams used to Oracle or SQL Server, PostgreSQL can look familiar enough that it feels safe to manage it in the same way. But proprietary systems encourage specific schemas, workflows, and habits that don't always translate well to PostgreSQL's architecture. Bringing those patterns into an open source environment means missing out on features that make PostgreSQL distinctive and, ultimately, keeps you stuck with the same constraints you were trying to move past.

The best path forward

To get the best results from PostgreSQL, it's important to embrace features designed specifically for it rather than falling back on habits from legacy systems. Advanced indexing methods such as BRIN, which accelerates queries on very large, sequentially ordered datasets, and GIN, which enables fast searches on complex data types like JSON, arrays, and text, can deliver major performance gains, while tools such as pg_stat_monitor make it possible to track query behavior and tune workloads proactively.

5. Neglecting proactive monitoring, causing silent performance decline and delayed issue detection

Slowdowns in PostgreSQL rarely happen all at once. More often, performance erodes gradually. An overlooked query here, a missing index there, and little by little those inefficiencies accumulate until performance drops and the system drags. By the time users complain, you're already in reactive mode, facing longer outages, higher costs, and far more stress than if those issues had been caught earlier through steady observation.

Proprietary vendors might push expensive monitoring packages as if they're the only way to stay ahead of issues, but that isn't the case. The PostgreSQL ecosystem already provides powerful tools that give deep visibility into performance, without the markup attached to proprietary add-ons.

The best path forward

One of the most effective ways to stay ahead of performance issues is to adopt open source monitoring solutions that offer full transparency without the licensing costs of proprietary add-ons. Establishing baseline performance metrics early makes it possible to detect when the system begins drifting from normal behavior, and setting up alerts ensures that small issues are addressed before they escalate.

Query analysis should also become a routine part of operations. The PostgreSQL community maintains mature, well-tested tools that provide the necessary visibility at a fraction of the cost of proprietary options.

Unlock PostgreSQL's Full Value

PostgreSQL delivers real value when it's treated as the open, adaptable system it was built to be. By steering clear of vendor lock-in, breaking away from legacy habits, and making full use of community-driven tools, organizations can unlock PostgreSQL's true potential and ensure their database strategy supports long-term growth.

Bennie Grant is COO of Percona

Hot Topics

The Latest

For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...

As an analyst who researches how IT organizations design, build, and operate their networks, I find that network data is a constant source of pain. Network teams struggle with data quality, fragmentation, authority, access, and trust. And these issues undermine everything they try to do. Here are the numbers: Only 45% of network teams are completely confident in the accuracy of their network source of truth, which documents the intent of their network ...

The 2026 Global Data Center Survey from Uptime Institute reveals an industry navigating workforce constraints, escalating outage expenses, even as rising costs remain the top concern for management teams ...

The next observability gap may not be in the code. It may be under the rack. That sounds strange until you think about how AI incidents actually feel in the middle of an investigation ... The application dashboard may be accurate. It may also be stopping at the wrong boundary. AI systems depend on software, but they also depend on a dense physical stack: racks, power paths, thermal margin, maintenance activity and, in many environments, liquid cooling. Those physical dependencies can change slowly before they look like a software incident ...

Certificate expiration is the rare outage you can see coming. Every TLS certificate carries the date it stops working, so the moment it will begin breaking connections is knowable in advance. That's what makes an expired certificate such a frustrating way to lose a service. What's changing now is how often that date comes around ...

Enterprises operate different combinations of workloads across cloud, hybrid and multicloud environments. For business-critical workloads, teams need to consider monitoring and observability early so they can detect health issues, investigate failures, and understand operational impact. Organizations place workloads on cloud platforms based on a combination of technical requirements, economics, existing dependencies, organizational standards, and business priorities. Their monitoring priorities therefore depend on what they operate and where those systems run. Those priorities will not look the same for every organization ...

Top-performing businesses prioritize data-driven decision making, enabling leaders to move from intuition and gut feel towards evidence-based judgment. But that judgment is only sound when the data underpinning decisions is accurate. With incident management, data accuracy is particularly important. Long-term revenue, customer trust, and operational stability depend on high-quality data that enables teams to quickly identify and address the root cause of major incidents. Against this backdrop, governance becomes a critical endeavor to ensure the right data drives the right action ...

In MEAN TIME TO INSIGHT Episode 26, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network compliance ... 

Most production autonomous agents do not run in a vacuum. They run inside cloud infrastructure: virtual machines, containers, pods, managed clusters or private servers. That is where most operations teams start monitoring. Is the VM alive? Is the container running? Did the pod restart? Is memory stable? Is CPU too high? Did the health check pass? Those signals are useful. They tell you whether the shell around the agent is alive. They do not tell you whether the agent inside is actually operational ...

Enterprise IT environments have never been more observable ... Yet many organizations still grapple with outages, lengthy incident resolution cycles, and increasing complexity. Most teams do not suffer from a shortage of data. They struggle to determine what deserves attention and what action to take next ... Enterprise IT operations must move beyond monitoring and visibility. The next stage of maturity is decision operations, an approach that helps teams make faster, better-informed decisions ...

Don't Fall Into These 5 PostgreSQL Traps

Bennie Grant
Percona

PostgreSQL promises greater flexibility, performance, and cost savings compared to proprietary alternatives. But successfully deploying it isn't always straightforward, and there are some hidden traps along the way that even seasoned IT leaders can stumble into.

In this blog, I'll highlight five of the most common pitfalls with PostgreSQL deployment and offer guidance on how to avoid them, along with the best path forward.

1. Mistaking proprietary forks for true open source, leading to costly vendor lock-in

Because PostgreSQL has become such a trusted open source database platform, some vendors trade on its name while quietly steering customers toward their own proprietary forks. They may advertise themselves as open source, but behind the scenes, they add exclusive extensions, altered code, or management layers.

The best path forward

When evaluating providers, scrutinize claims of "100% compatibility" and verify their releases stay aligned with the PostgreSQL Global Development Group. Be cautious of distributions that depend on closed extensions.

It's also worth asking how much the vendor gives back to the PostgreSQL community. Companies that mostly consume without giving back often rely on selling proprietary add-ons.

2. Underestimating the importance of tailored high availability and disaster recovery strategies

Commercial database vendors often present their high availability and disaster recovery tools as plug-and-play, suggesting everything will run automatically. In reality, those promises of "enterprise-grade uptime" and "built-in resilience" rarely come with clear definitions, and the simplified interfaces or automated failover they showcase usually depend on rigid architectures that don't adapt to the unique needs of your business.

The real shortcomings emerge in moments of crisis. Hardware failures, network outages, or data corruption quickly expose how inflexible these systems really are. Instead of seamless continuity, you may face long outages, lost information, and frustrated customers. And to make matters worse, the fine print of SLAs might exclude exactly the kinds of scenarios you expected to be protected against.

The best path forward

A more resilient approach is to rely on open source high availability frameworks such as  Patroni, which can be adapted to fit the unique demands of your organization. For backup and recovery, community-tested tools such as pgBackRest provide incremental and verifiable protection without the opacity of proprietary "black box" systems.

It's equally important to run failover drills regularly under realistic workloads. While some commercial vendors downplay or even discourage this practice due to the limitations of their own architectures, testing in real conditions is the only way to ensure your DR plan will hold up when it matters most.

3. Paying extra for security features PostgreSQL provides natively

Proprietary database vendors sometimes exploit outdated beliefs about open source security, strategically framing their expensive security bundles as the only safe choices for meeting strict compliance rules.

The reality is that when set up properly, PostgreSQL already delivers strong protections on par with, and sometimes exceeding, those found in commercial databases. These include built-in features such as SSL/TLS encryption for data in transit, role-based permissions, and audit logging. Marketing spin often hides this fact, leaving teams unaware that many of the features they're paying for are already available at no extra cost.

The best path forward

Pairing PostgreSQL's built-in security capabilities with guidance from PostgreSQL specialists ensures that your system is configured to meet regulatory standards without depending on costly proprietary layers. Requesting a side-by-side comparison between a vendor's security bundles and PostgreSQL's native features also makes the price gap clear.

4. Applying incompatible legacy database designs that hamper PostgreSQL's potential

For teams used to Oracle or SQL Server, PostgreSQL can look familiar enough that it feels safe to manage it in the same way. But proprietary systems encourage specific schemas, workflows, and habits that don't always translate well to PostgreSQL's architecture. Bringing those patterns into an open source environment means missing out on features that make PostgreSQL distinctive and, ultimately, keeps you stuck with the same constraints you were trying to move past.

The best path forward

To get the best results from PostgreSQL, it's important to embrace features designed specifically for it rather than falling back on habits from legacy systems. Advanced indexing methods such as BRIN, which accelerates queries on very large, sequentially ordered datasets, and GIN, which enables fast searches on complex data types like JSON, arrays, and text, can deliver major performance gains, while tools such as pg_stat_monitor make it possible to track query behavior and tune workloads proactively.

5. Neglecting proactive monitoring, causing silent performance decline and delayed issue detection

Slowdowns in PostgreSQL rarely happen all at once. More often, performance erodes gradually. An overlooked query here, a missing index there, and little by little those inefficiencies accumulate until performance drops and the system drags. By the time users complain, you're already in reactive mode, facing longer outages, higher costs, and far more stress than if those issues had been caught earlier through steady observation.

Proprietary vendors might push expensive monitoring packages as if they're the only way to stay ahead of issues, but that isn't the case. The PostgreSQL ecosystem already provides powerful tools that give deep visibility into performance, without the markup attached to proprietary add-ons.

The best path forward

One of the most effective ways to stay ahead of performance issues is to adopt open source monitoring solutions that offer full transparency without the licensing costs of proprietary add-ons. Establishing baseline performance metrics early makes it possible to detect when the system begins drifting from normal behavior, and setting up alerts ensures that small issues are addressed before they escalate.

Query analysis should also become a routine part of operations. The PostgreSQL community maintains mature, well-tested tools that provide the necessary visibility at a fraction of the cost of proprietary options.

Unlock PostgreSQL's Full Value

PostgreSQL delivers real value when it's treated as the open, adaptable system it was built to be. By steering clear of vendor lock-in, breaking away from legacy habits, and making full use of community-driven tools, organizations can unlock PostgreSQL's true potential and ensure their database strategy supports long-term growth.

Bennie Grant is COO of Percona

Hot Topics

The Latest

For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...

As an analyst who researches how IT organizations design, build, and operate their networks, I find that network data is a constant source of pain. Network teams struggle with data quality, fragmentation, authority, access, and trust. And these issues undermine everything they try to do. Here are the numbers: Only 45% of network teams are completely confident in the accuracy of their network source of truth, which documents the intent of their network ...

The 2026 Global Data Center Survey from Uptime Institute reveals an industry navigating workforce constraints, escalating outage expenses, even as rising costs remain the top concern for management teams ...

The next observability gap may not be in the code. It may be under the rack. That sounds strange until you think about how AI incidents actually feel in the middle of an investigation ... The application dashboard may be accurate. It may also be stopping at the wrong boundary. AI systems depend on software, but they also depend on a dense physical stack: racks, power paths, thermal margin, maintenance activity and, in many environments, liquid cooling. Those physical dependencies can change slowly before they look like a software incident ...

Certificate expiration is the rare outage you can see coming. Every TLS certificate carries the date it stops working, so the moment it will begin breaking connections is knowable in advance. That's what makes an expired certificate such a frustrating way to lose a service. What's changing now is how often that date comes around ...

Enterprises operate different combinations of workloads across cloud, hybrid and multicloud environments. For business-critical workloads, teams need to consider monitoring and observability early so they can detect health issues, investigate failures, and understand operational impact. Organizations place workloads on cloud platforms based on a combination of technical requirements, economics, existing dependencies, organizational standards, and business priorities. Their monitoring priorities therefore depend on what they operate and where those systems run. Those priorities will not look the same for every organization ...

Top-performing businesses prioritize data-driven decision making, enabling leaders to move from intuition and gut feel towards evidence-based judgment. But that judgment is only sound when the data underpinning decisions is accurate. With incident management, data accuracy is particularly important. Long-term revenue, customer trust, and operational stability depend on high-quality data that enables teams to quickly identify and address the root cause of major incidents. Against this backdrop, governance becomes a critical endeavor to ensure the right data drives the right action ...

In MEAN TIME TO INSIGHT Episode 26, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network compliance ... 

Most production autonomous agents do not run in a vacuum. They run inside cloud infrastructure: virtual machines, containers, pods, managed clusters or private servers. That is where most operations teams start monitoring. Is the VM alive? Is the container running? Did the pod restart? Is memory stable? Is CPU too high? Did the health check pass? Those signals are useful. They tell you whether the shell around the agent is alive. They do not tell you whether the agent inside is actually operational ...

Enterprise IT environments have never been more observable ... Yet many organizations still grapple with outages, lengthy incident resolution cycles, and increasing complexity. Most teams do not suffer from a shortage of data. They struggle to determine what deserves attention and what action to take next ... Enterprise IT operations must move beyond monitoring and visibility. The next stage of maturity is decision operations, an approach that helps teams make faster, better-informed decisions ...