# Why Delphi Became an Old Technology

> A personal engineering perspective from someone who has worked with Delphi, examining how it moved from highly productive desktop RAD to a narrower position in modern open-source, web, mobile, Linux and server-side software ecosystems.

- Author: Muhammet Ali Köker
- Language: en
- Canonical: https://alikoker.com.tr/en/why-delphi-became-an-old-technology
- Translation: https://alikoker.com.tr/delphi-neden-eski-bir-teknoloji-haline-geldi
- Published: 2019-11-18T12:00:00+03:00
- Modified: 2026-09-06T20:25:00+03:00
- Verified: 2026-09-06T20:25:00+03:00
- Type: article

I no longer use Delphi in my day-to-day work. I still look at it occasionally when a new release appears, an old component name turns up, or I have to touch software written in Delphi years ago. Today I no longer judge it mainly by syntax or by the IDE; what matters more is how many of the problems it once solved exceptionally well still sit at the centre of software development.

I would not choose Delphi today as the default technology for a substantial new project. That is not because a new project cannot be built with Delphi. Windows applications, database access, HTTP services, Android and iOS targets, Linux binaries and concurrent workloads are all technically possible.

I no longer evaluate a programming language only by asking whether it can perform a task. C and C++ can solve an enormous range of problems as well, as can Java, C#, Python and many other languages. The difference appears in how much surrounding machinery has to be carried with the solution. That is also what makes Delphi feel old to me.

By old I do not mean abandoned or non-functional. RAD Studio continues to receive releases, operating-system updates and new platform targets. What feels old is the centre of gravity of the language and development environment. Delphi remains most natural around forms, components, events, datasets and desktop applications, while much of the industry moved long ago toward web systems, services, distributed architectures, Linux, containers, open package ecosystems and the native toolchains of mobile platforms.

## Why it no longer comes to mind for a new project

When I build a new service in Java or C#, I expect to find mature answers for HTTP, dependency management, testing and telemetry around the language. Python has a similar effect in data, scientific computing and AI. When work moves closer to operating systems, hardware, embedded software or a performance boundary, decades of open C and C++ infrastructure are immediately available.

With Delphi the same questions can turn earlier into another question: is there a Delphi equivalent? That distinction may look small at first, but it grows over the lifetime of software. The cost of a system is not only the number of days needed for the first release; five years later an authentication mechanism changes, a vendor SDK changes, an operating system is updated, a vulnerable dependency must be replaced, a CI environment moves and another engineer joins the project.

Delphi was exceptionally good in a world where a Windows machine, a relational database and a desktop interface could constitute most of an enterprise application. A `TQuery`, `TDataSource` and `TDBGrid` could turn into a working business screen within hours. Compared with the effort required to build equivalent Windows interfaces in C++ at the time, the productivity was remarkable.

The problem was not rapid development itself. The problem was that the structure created for rapid development could keep growing for years and gradually become the architecture.

## When the form becomes the application

What feels most foreign when I return to old Delphi code is not Pascal syntax. Object Pascal remains readable. The larger difference is in dependencies that once felt completely normal.

Putting a query on a form was easy, connecting a `DataSource` was easy, and running business logic in a button event felt natural. Accessing another form through a global variable was equally easy.

```pascal
MainForm.Edit1.Text := Value;
DataModule1.Query1.Open;
```

The code is short, but the dependency is not. Behind those lines may be the UI lifecycle, global objects, database connections, form-creation order and shared application state. In a small program that may be harmless; in a large application it becomes a problem when a method signature no longer tells me what the method actually depends on.

Delphi does not prevent layered architectures, interfaces or dependency injection. Projects such as Spring4D have existed for years to improve exactly these areas. But when choosing a platform I care not only about what can be done, but about what the platform makes natural. Classic Delphi RAD makes development very fast, and it can make tightly coupled code equally fast.

## DataSet is still a good idea in the right place

I do not consider Delphi's database components a mistake. For desktop database software it is easy to understand why they became so popular.

```text
Database
   |
DataSet
   |
DataSource
   |
DBGrid
```

Turning data into an editable interface with only a few objects is still impressive. In larger systems I usually want a different boundary:

```text
Database
   |
Persistence
   |
Domain
   |
Application
   |
API / UI
```

The first produces a result quickly; the second keeps database state farther away from presentation code. Many problems I encounter in old Delphi applications are therefore not defects in the language itself. They are the long-term traces of a model that was once extremely productive.

## Memory management

When I worked with Delphi, this was completely ordinary:

```pascal
Obj := TObject.Create;
try
  Obj.Execute;
finally
  Obj.Free;
end;
```

The model remains easy to understand and gives deterministic lifetime. After spending years in other language ecosystems, however, continuously tracking `Create/Free` pairs feels increasingly like work unrelated to the application problem.

The absence of a garbage collector does not itself make a language old; Rust demonstrates the opposite. The distinction is how much ownership responsibility can be understood and enforced by the compiler. Rust attempts to move ownership into compile-time reasoning, while Delphi still leaves a substantial part of correct object lifetime to the programmer.

Leaks, incorrect ownership, dangling references and `nil` access are old classes of failures. What interests me in a modern language is not whether correct code can be written, but how much incorrect code the compiler can reject. A Delphi object reference may be `nil` as an ordinary runtime condition, while Kotlin distinguishes `T` and `T?`, Rust uses `Option<T>`, and modern C# performs nullable-reference analysis.

## Threads exist; creating a thread is not the question

Concurrent programming is not new to Delphi. `TThread` has been available for years, followed by the Parallel Programming Library and `TTask`. Saying that Delphi has no multithreading support would simply be inaccurate.

The difference is how deeply concurrency is integrated into the overall programming model. Java has `ExecutorService`, `ForkJoinPool`, `CompletableFuture`, concurrent collections and now virtual threads inside one large ecosystem. C# has built `Task` and `async/await` deeply into the language and framework; Go made concurrency part of its identity, while Rust connects some concurrency safety to its type system.

Equivalent work can be constructed in Delphi. But especially for I/O-heavy server software, it matters when language, runtime, libraries, cancellation, sockets and debugging have grown around a common asynchronous model. `async/await` is not merely convenient syntax; it represents a shared model for cancellation, error propagation, scheduling, I/O and framework behaviour.

## Native code no longer settles the argument

One of the arguments still commonly made in favour of Delphi is that it produces native executables. That is true and still useful, but it is no longer unusual. C and C++ are already native, Rust and Go produce native binaries, Swift is native, and .NET has increasingly capable AOT options.

JVM and CLR implementations have spent decades developing JIT compilation, profiling, garbage collection and runtime optimisation in another direction. I cannot infer the performance of software from the language name; algorithms, memory access, allocation patterns, I/O, cache locality, locking and library quality often matter more.

Native compilation can still be an advantage, but it is not the same as modernity. The more important question today is not whether the compiler produces a binary, but what development and operational ecosystem surrounds that binary.

## The web did not wait for Delphi

Serious web services can be built in Delphi. WebBroker has existed for a long time, and modern open-source projects such as DelphiMVCFramework provide REST, JWT, middleware, ORM, WebSocket and Redis integrations.

The important question is not whether individual features exist. While Spring grew around Java, ASP.NET around .NET, Django and FastAPI around Python, and the Node ecosystem around JavaScript, Delphi never created an equivalent centre of gravity for web development.

A framework can be written, but an ecosystem does not emerge simply because a framework exists. It grows from thousands of independent developers, companies, libraries, documentation pages, bug reports, integrations and production deployments. Delphi achieved that kind of accumulation on the desktop; it did not achieve comparable weight on the web.

## Mobile support without a comparable mobile ecosystem

FireMonkey interested me when it appeared. A common code base targeting several platforms is naturally attractive, and Delphi still targets Android and iOS.

But there is a difference between Delphi technically supporting mobile platforms and the mobile industry broadly choosing Delphi. Android evolved around Kotlin and Java, iOS around Swift; Flutter built its own ecosystem, and React Native benefits from the scale of JavaScript.

When a platform changes an API or a vendor publishes a new SDK, the technologies supported first are revealing. Kotlin, Swift, JavaScript, Java, C#, Python or C++ examples are routine; Delphi examples are less common. A binding can be written, a wrapper can be created and native APIs can be called, but technical possibility is not the same as low engineering cost.

## Linux support and belonging to the Linux ecosystem are different things

Delphi can now compile server-side software for Linux. That is a meaningful technical improvement, but after spending years with Linux systems I find it difficult to define platform support only as the ability to produce an executable.

The Linux development environment includes shell tooling, package managers, containers, standard build systems, open-source services, distributed-system tooling, profilers and observability infrastructure. Go, Java, C/C++, Rust, Python and increasingly .NET are routine participants in that world.

Delphi reached Linux, but the centre of gravity of the Linux ecosystem did not move around Delphi. Again, target support and ecosystem membership are different things.

## Package management is more than downloading a package

Delphi has GetIt today. That is better than the old routine of downloading a component, running an installer, registering a package in the IDE and editing Library Path.

But after Maven Central, NuGet, npm or PyPI, it is difficult to treat these ecosystems as equivalent. Major package repositories are now measured in millions of components. They do not count exactly the same thing, so I do not treat them as a direct language market-share comparison, but Delphi's package and component ecosystem is clearly not on the same scale as those central repositories.

A Java project moved to a new machine normally restores Maven or Gradle dependencies. NuGet serves a similar role in .NET, and Python and JavaScript developers have comparable expectations. In older Delphi projects, the real dependency definition could leak into installed components, DCU/BPL versions and IDE paths.

Seeing `Unit X not found` in an old project was not always simply a message about a missing file. Sometimes it meant reconstructing part of the machine on which the software had originally been built. That kind of environment coupling is something I prefer not to create deliberately in a new system.

## Looking at GitHub

When I occasionally check what is happening in Delphi, I also look at GitHub. DelphiMVCFramework, Spring4D and several other good projects are there, and some are clearly production-quality.

Their presence does not change the overall scale. GitHub's 2025 Octoverse data places TypeScript, Python, JavaScript, Java, C#, PHP, C++, Shell, HCL and Go among the leading languages; Delphi is not in the top ten. GitHub popularity does not measure language quality, and it would be absurd to judge every established language by a trending chart.

It still matters for new-project economics. GitHub is not merely source hosting; it contains issue histories, examples, CI configurations, real failures, pull requests, integrations and an enormous body of engineering memory. Delphi does not occupy that memory at anything close to the scale of Java, C#, Python, JavaScript or C++.

## AI tools make the difference more visible

A few years ago a small community mainly meant fewer Stack Overflow answers and fewer search results. The same scarcity now appears in another place.

Coding models, retrieval systems and AI tools embedded in IDEs benefit from public source code, documentation, issues, examples and technical discussions. The public evidence available for a widely used Java library is not comparable to the material available for an uncommon commercial Delphi component.

This does not mean an AI system cannot write Delphi. The problem becomes clearer in the long tail: old component versions, compiler-specific behaviour, DFM details and proprietary APIs. As source material becomes scarce, the model has less evidence and more room to guess.

A large open-source ecosystem no longer helps only humans find answers. It also creates machine-readable technical memory, which makes the disadvantage of a smaller ecosystem more visible than it used to be.

## Programming languages at university

We used Robert W. Sebesta's *Concepts of Programming Languages* in a university programming-languages course. Because I had already written Delphi, I naturally looked for where it fitted into the language families and design ideas discussed in the book.

What I remember is that Delphi was not a central language in that discussion. The 12th edition, published in 2018, makes the contrast more interesting because it explicitly added material on Swift and Python while removing some material considered outdated. Its structure is organised around language evolution, type systems, object orientation, concurrency, functional programming and logic programming, and Delphi is not a prominent reference language in that contemporary comparison.

One textbook does not determine the importance of an industrial technology. Years later, however, the same pattern appears in open course material from universities such as Stanford and MIT. Stanford's current Programming Languages course discusses Haskell and Rust while covering type systems, algebraic data types, concurrency, metaprogramming and semantics; MIT's introductory material uses Python and also exposes students to Julia, MATLAB, Java and C/C++.

I am not surprised not to find Delphi there. A language's academic value is not measured only by whether universities teach it, but this is still a useful signal when trying to understand where new programmers are being trained. Pascal once had a strong educational role; Delphi did not turn that historical position into an equally strong place in the modern language ecosystem.

## Licensing

One detail still makes Delphi feel tied to an older software economy: licensing. Community Edition is useful, and students, hobbyists and very small developers can use Delphi without paying for a commercial licence.

The current official conditions still include an annual revenue threshold of USD 5,000 and limits for larger development teams. Community Edition is licensed for a one-year term, and capabilities such as remote database connectivity and Linux server deployment are tied to higher commercial editions.

All of these rules can make commercial sense. My question is different: with OpenJDK, .NET SDK, GCC, Clang, Go, Rust and Python available beside it, why would I voluntarily add compiler and IDE licensing policy as a design variable in a new project?

In the 1990s a good compiler and IDE were substantial commercial products in their own right. By 2026 it is ordinary for compilers, runtimes, language servers, debuggers, package infrastructure and frameworks to be largely open source. Delphi's licensing model may still work as a business model, but it belongs to a development-tool economy that is clearly different from today's open ecosystems.

## The Turkish Ministry of Education and one million students

A 2020 agreement between Türkiye's Ministry of National Education and BTG brought Delphi into vocational and technical education on an unusual scale. The event is sometimes described online as the ministry purchasing one million Delphi licences, but that is not what the official announcement says.

The programme aimed to make Delphi available free of charge to roughly one million students in more than 1,600 vocational and technical schools and included teacher training and laboratory work. That distinction matters; there is no reason to invent a procurement claim without evidence.

The fact that the licence was free does not remove my main objection. Student time, curriculum time, teacher training, laboratory capacity and institutional attention all have opportunity cost. At the scale of one million students, the question is not the licence invoice but why Delphi was selected.

If the objective was to teach programming fundamentals, there were open alternatives with broader ecosystems. If employability was the objective, larger industrial ecosystems were available. If mobile was the target, the native Android and iOS languages existed; the web had already consolidated around other platforms, and Python's direction in data science and machine learning was already obvious in 2020.

Delphi's Pascal heritage makes its syntax relatively approachable, and that is an advantage. It is not enough for me to justify the opportunity cost of a technology choice affecting one million students. Students do not learn only `if`, `for` and functions; they use package managers, browse repositories, read other people's code, integrate libraries, debug real failures, learn CI and eventually enter a technical community.

## The unusual place of Delphi in education

Pascal has a legitimate historical place in computer-science education. Niklaus Wirth's language and Delphi as a commercial RAD platform should not be treated as the same educational proposition.

The fact that Pascal was designed with teaching in mind does not automatically prove that a commercial Delphi toolchain is the best current educational investment at national scale. I also do not believe educational languages must simply follow job-market rankings; Scheme, Haskell or OCaml may be extremely valuable precisely because they expose programming-language concepts clearly.

The difference is purpose. Those languages are often selected to make semantics, functional composition, type systems or other ideas visible. The educational argument for Delphi tends instead to rely on approachable Pascal syntax, rapid GUI construction and RAD productivity.

Those are useful qualities. If I were teaching a programming-languages course today and wanted to discuss type systems, semantics, functional programming, concurrency or memory safety, Delphi would not be my first example.

## Vendor history and long-lived software

Delphi's corporate history moved through Borland, the CodeGear organisation, Embarcadero and later the Idera group. This is sometimes simplified into a claim that Delphi was sold four times, which is not an accurate description of every organisational transition.

CodeGear originated as Borland's developer-tools division before the business was acquired by Embarcadero, which later became part of Idera. The number of names matters less to me than the engineering consequence.

For software expected to live ten or twenty years, the compiler, IDE, framework and major components may all depend on the roadmap of a commercial vendor. I have no general objection to commercial software; long-running systems routinely depend on commercial databases, operating systems, hardware and tooling.

The dependency simply has to be priced. A Delphi application can depend not only on Delphi source but on a particular RAD Studio generation, a component suite, BPL/DCU compatibility and local IDE configuration. Having encountered that kind of historical coupling, I do not deliberately create it in a new system unless Delphi provides a very specific compensating advantage.

## Why FireMonkey did not change my conclusion

FireMonkey was an important attempt to move Delphi beyond its Windows desktop boundary. I do not underestimate the engineering difficulty of targeting Windows, macOS, Android and iOS from one framework.

I still look at the outcome. Years after FireMonkey arrived, Delphi remains exceptional rather than normal in mainstream mobile software, while Flutter, React Native and native platform ecosystems are far more visible in cross-platform and mobile development.

A target list and market adoption are different things. Producing a binary for a platform is the first step; having developers, SDK vendors, library authors, employers and new graduates cluster around that platform is the second.

Delphi achieved the first. It did not achieve the second at comparable scale.

## I still would not immediately rewrite an old Delphi application

None of this means that a large working Delphi system should be rewritten simply because Delphi is old. That would confuse a new-project decision with a migration decision.

A twenty-year-old application contains more than algorithms. It contains resolved bugs, database oddities, user expectations, forgotten edge cases and business rules that may exist nowhere except in source code.

It is easy to look at hundreds of lines of event code in an old form and call it bad architecture. It is more expensive to rewrite it and rediscover half of the production failures that had already been solved over fifteen years.

With an existing Delphi system I would first establish boundaries. I would preserve the stable core, while new integrations, web layers, mobile clients, reporting, search or compute-heavy components could be separated into other technologies where useful. Only when the old part had actually become small enough would I ask whether replacing it was worth the risk.

## Delphi's strongest argument today

The most convincing reason I hear for Delphi today is often simply: "This system is already Delphi." That can be a very good reason.

If the team knows the language, the application has run reliably for years, there is a large VCL investment, Windows desktop is still the target and the software solves the business problem, rewriting it because another language is fashionable makes little sense. A new project has none of those advantages; Delphi then competes with the alternatives from zero.

For me the result has been stable for years. Even for a new Windows desktop application I would first consider C#/.NET and the other current options. Java, .NET or Go feel more natural for backend work; C/C++ or Rust fit systems-level work; Python dominates much of the data and AI work I encounter; for mobile I would look first at the platform-native toolchains or the broadly adopted cross-platform ecosystems.

Delphi returns to the table only when the requirement fits one of Delphi's remaining strengths unusually well. That is an odd position for a language I used in the past; opening the IDE still feels familiar, and the Object Inspector, form designer, units, `begin/end`, properties and events require almost no conscious recall.

Then I close it and return to the systems I work with today. The main difference is not syntax; the world changed. Delphi changed too, but it did not build comparable weight in the places toward which the world moved. That is what makes Delphi old to me: not that it stopped working, but that it is no longer one of the first tools I think of when a new problem arrives.

---

### References

- Robert W. Sebesta, *Concepts of Programming Languages*, 12th Edition, Pearson, 2018: https://www.pearson.com/en-us/subject-catalog/p/concepts-of-programming-languages/P200000003361/9780134997186
- GitHub, *Octoverse 2025 – Top Programming Languages*: https://github.blog/news-insights/octoverse/octoverse-a-new-developer-joins-github-every-second-as-ai-leads-typescript-to-1/
- Sonatype, *State of the Software Supply Chain 2026 – Software Infrastructure Growth*: https://www.sonatype.com/state-of-the-software-supply-chain/2026/software-infrastructure-growth
- Stanford University, CS 242 – Programming Languages: https://explorecourses.stanford.edu/search?q=CS242
- MIT OpenCourseWare, Introductory Programming: https://ocw.mit.edu/collections/introductory-programming/
- MIT OpenCourseWare, Language Specific Programming Courses: https://ocw.mit.edu/course-lists/language-specific-programming-courses/
- Embarcadero, Delphi Community Edition FAQ: https://www.embarcadero.com/products/delphi/starter/faq
- Embarcadero, Reasons to Upgrade Delphi: https://www.embarcadero.com/products/delphi/starter/top-upgrade-reasons
- Embarcadero RAD Studio Platform Status: https://docwiki.embarcadero.com/PlatformStatus/en/Main_Page
- DelphiMVCFramework: https://github.com/danieleteti/delphimvcframework
- Spring4D: https://github.com/spring4d/spring4d
- Republic of Türkiye Ministry of National Education, software education programme for vocational-school students: https://www.meb.gov.tr/1-milyon-meslek-lisesi-ogrencisine-yazilim-egitimi/haber/20138/tr

## Cite This Work

Köker, M. A. (2019). Why Delphi Became an Old Technology. alikoker.com.tr. https://alikoker.com.tr/en/why-delphi-became-an-old-technology

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