PostgreSQL on Ubuntu 24.04 LTS

My main use case for PostgreSQL on Ubuntu  is to store data, especially telemetry data and customer data. I had a client whose telemetry data was coming online on one of their on-premises devices. I proposed spinning off an instance of PostgreSQL on Ubuntu  on one of the incidents and used it to store on-premises data. The main objective was to keep the data on-premises for that particular device and that particular infrastructure. This helped me to keep the data on-premises rather than on cloud.

We also proposed PostgreSQL on Ubuntu on our onsite databases as well. It helped us to analyze our data in near-real-time, which was a very good use case.

PostgreSQL on Ubuntu offers data caching, on-premises data storage, data security, and I can write, store, and analyze data on the PostgreSQL on Ubuntu instance. That is really helpful for me.

I rely on on-premises and data caching the most because data caching helps to reduce the latency for any systems I develop. On-premises makes data security and data privacy its utmost goal, and both of them are maintained.

PostgreSQL on Ubuntu has definitely impacted my organization to analyze their data. Some of the clients for my particular organizations are preferring on-premises data storage. PostgreSQL on Ubuntu gives me the ability to help them keep their data on-premises, but at the same time, I can go onto their jump host to their servers and analyze their data. That is really helpful.

Data caching, particularly PostgreSQL on Ubuntu data caching, helped to reduce our average latency. When I was making a few data analytics, I got to know that PostgreSQL  caching helped me to save five milliseconds of latency on every call, which is a lot for user experience as well as productivity. That is very helpful.

PostgreSQL on Ubuntu can be improved by adding more diverse components and ad hoc features like data analysis and data analysis models on-premises. For example, creating Jupyter notebooks or analyzing data directly on PostgreSQL  would be a much nicer use case rather than just having a simple database. Adding capabilities of AI as well as RAG as well as MCT would really help PostgreSQL on Ubuntu nowadays.

PostgreSQL on Ubuntu's accuracy and reliability of output is pretty naive from my perspective. It should be more controlling and more customizable.

I have been using PostgreSQL on Ubuntu for five years.

PostgreSQL on Ubuntu is stable in my experience.

I would rate PostgreSQL on Ubuntu's scalability a ten out of ten as I find it very amazing. It can be easily scalable with Docker  and Kubernetes .

I think the customer support for PostgreSQL on Ubuntu is very nice. I really didn't have to go with customer support at any time, but I think it would be nice.

I didn't use any other solution before PostgreSQL on Ubuntu. I just used PostgreSQL on Ubuntu.

The pricing was pretty decent for PostgreSQL on Ubuntu. I really appreciated it.

I would say money saved and time saved are the most viable buy-ins to use PostgreSQL on Ubuntu because it really helped me to drill down the cost of employees as less workforce is needed.

We evaluated Oracle DB, but while Oracle DB is good, at the same time, it is pretty naive compared to PostgreSQL on Ubuntu.

I would rate PostgreSQL on Ubuntu an eight out of ten. The pace of development is very high. Adding these new features like data science models, semantic models, as well as AI capability would be really better if it were on PostgreSQL on Ubuntu.

PostgreSQL on Ubuntu's governance and security is really nice. I love the governance and security that PostgreSQL provides. That is my best buy-in for PostgreSQL on Ubuntu.

If you are really looking into some data management systems that are much more lightweight as well as capable and higher in performance, you should definitely go with PostgreSQL on Ubuntu. I gave this review a rating of eight out of ten.

The primary use case for PostgreSQL on Ubuntu  is storing and managing structured financial data extracted from scanned documents through our AI pipeline. When we processed an invoice or a trial balance through our OCR and LLM system, PostgreSQL on Ubuntu  became the persistent layer where all that extracted data lived, including account codes, amounts, dates, and confidence scores from all the models. The FastAPI backend would query PostgreSQL  to retrieve those records, and chartered accountants would use them in the system to validate and map those extracted line items. If someone needed to trace where a particular account entry came from, PostgreSQL  had the complete audit trail and raw extracted data ready to query.

PostgreSQL on Ubuntu integrated seamlessly with the rest of our stack. We used it alongside n8n  automation workflows running on Docker , and those n8n  instances would write processed data directly into PostgreSQL tables. The database became their central hub where financial data flowed through multiple stages of the pipeline, from initial extraction through LLM classification, through trial balance mapping, all the way to final storage. We also leveraged PostgreSQL on Ubuntu’s JSONB columns quite extensively since our LLM outputs were semi-structured JSON. Being able to store those flexible JSON objects directly in the database without needing a separate document store was invaluable. It simplified our architecture and made querying and data retrieval much more straightforward when we needed to filter or aggregate results for reporting.

PostgreSQL on Ubuntu is deployed on-premises on Hostinger  in our organization.

The standout features PostgreSQL on Ubuntu offers were three things. First, JSONB support was huge. Since our LLM pipeline generated semi-structured JSON outputs with extracted fields and confidence scores, being able to store and query that JSON directly in PostgreSQL on Ubuntu without needing a separate document store was a massive win. It simplified our entire architecture. Second was reliability and stability on Ubuntu . We ran PostgreSQL on Ubuntu on a Linux server in production and it was rock solid. We never had unexpected crashes or data integrity issues, even under heavy batch processing loads. The backup tooling with pg_dump also integrated seamlessly into our automated workflows, so we had confidence our data was always safe. Third, indexing and query performance was excellent. When the FastAPI backend needed to retrieve specific financial records or filter by account codes for our trial balance mapping system, queries stayed fast and consistent even as the dataset grew. That performance directly translated to a snappier experience for the chartered accountants using the system, which mattered significantly.

The impact of PostgreSQL on Ubuntu was tangible for our organization. On the reliability front, once we had PostgreSQL on Ubuntu as our structured data layer, we eliminated a lot of manual data validation work. Before that, extracted financial data had nowhere consistent to land, so it was error-prone. With PostgreSQL on Ubuntu in place, we had a clean, queryable store that made validation straightforward. On the metrics side, the full automation pipeline, which PostgreSQL on Ubuntu was central to, achieved a 70% reduction in manual data entry effort for our chartered accountant clients. Instead of manually re-entering invoice or trial balance data, the system extracted it, stored it cleanly in PostgreSQL on Ubuntu, and made it immediately available for review and mapping. That was a massive productivity gain. On cost, we also saw benefits from not needing separate document stores or complex caching layers. PostgreSQL on Ubuntu handled both structured data storage and semi-structured JSON in one place, which simplified our infrastructure and reduced operational overhead. The reliability also meant fewer debugging cycles and data recovery incidents, which translated to less engineering time spent on firefighting and more time on feature extraction.

The way I measured that 70% reduction in manual data entry was straightforward. We tracked the time chartered accountants spent manually entering financial data before and after our full automation pipeline went live. We examined a sample of their typical workflows, such as processing and trial balancing or a set of invoices, and compared how long it took them to do that work manually versus using our system end-to-end. The 70% figure came from that comparison. The system handled extraction, classification, and mapping automatically, so they only needed to do light validation rather than full manual data entry. It was not a rigorous academic study with control groups.

Several things come to mind for improvements in PostgreSQL on Ubuntu. First, the monitoring and observability experience on Ubuntu  could be smoother. Setting up proper visibility into query performance, slow query logs, and connection pool statistics requires additional tools such as pg_stat_statements or external monitoring solutions. It would be helpful if PostgreSQL on Ubuntu shipped with slightly more user-friendly native dashboards built-in, especially for developers who are not dedicated database administrators. Second, native vector similarity search would be valuable. We were doing semantic document retrieval as part of our pipeline, so we ended up using Pinecone  as a separate vector database alongside PostgreSQL on Ubuntu rather than keeping everything in one system. PostgreSQL on Ubuntu has some emerging vector capabilities, but if native vector similarity search were more mature and performant out of the box, it would allow consolidating the architecture and reducing operational complexity. Additionally, full-text search, while functional, required extra configuration for our financial document use case. Having more intuitive defaults for that would lower the barrier to entry for search-heavy applications.

I used PostgreSQL on Ubuntu throughout my time at Radiant Services, approximately one and a half years of hands-on production experience.

PostgreSQL on Ubuntu is stable.

The customer support for PostgreSQL on Ubuntu is quite responsive. When I needed help with my vector search, I contacted them, and they provided substantial assistance.

On the integration side, PostgreSQL on Ubuntu played well with our broader tech stack. The async driver we used, asyncpg, integrated smoothly with FastAPI, so our backend could handle concurrent requests efficiently without blocking on database calls. That was important when we were processing multiple documents in parallel. On extensions, we did not lean heavily into custom PostgreSQL on Ubuntu extensions, but the fact that they are available and well-maintained is reassuring for future use cases. On security, the role-based access control and pg_hba.conf gave us fine-grained control over who could access what, which was critical when handling sensitive financial data for chartered accountants. We could lock down access per application user and audit everything. PostgreSQL on Ubuntu’s strong ACID compliance meant we could trust data consistency, which is non-negotiable when dealing with financial records where accuracy is essential.

I give PostgreSQL on Ubuntu a rating of 8 out of 10. I chose this rating because there are improvements needed, such as native vector similarity search and smoother monitoring and observability experience on Ubuntu, particularly for developers who are not dedicated database administrators.

My advice to others looking into using PostgreSQL on Ubuntu would focus on connection pooling documentation and tooling, which is quite good. If you are building an AI or LLM-based application that produces structured or semi-structured data, which is increasingly common, PostgreSQL on Ubuntu is a genuinely strong choice. It is production-grade, battle-tested, and it handled our financial document processing workloads extremely well. My advice would be to use JSONB columns early if your outputs are schema-flexible, set up connection pooling with pgBouncer from day one, and if you need semantic search, combine PostgreSQL on Ubuntu with a vector database such as Pinecone  rather than trying to consolidate everything into one system.

Also, automate your backups with pg_dump as part of your CI/CD setup from the start. Overall, PostgreSQL on Ubuntu is very good, and I am genuinely impressed with how reliable and performant it was in our production environment. It scaled well for our use case. As our document volume grew over time, PostgreSQL on Ubuntu handled increased load without requiring major architectural changes. Proper indexing and query optimization kept performance consistent, and the fact that it runs efficiently on Ubuntu meant we could scale vertically by adjusting server resources without changing much in our application layer. For teams expecting data growth, which is almost inevitable in AI-driven document processing, PostgreSQL on Ubuntu is an excellent choice.