Best Midjourney Alternatives in 2025
Infrastructure
11.09.2025
7 min read
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Midjourney is one of the most popular AI networks for image generation. The service has established itself as a leader in the field of generative AI. However, the existence of a paid subscription and access limitations (for example, the requirement to use Discord or lack of support in certain regions) increasingly prompts users to consider alternatives. We have compiled the best services that can replace Midjourney, from simple tools to professional solutions.
Why Are Users Looking for a Midjourney Alternative?
Midjourney is a powerful tool, but it has its drawbacks:
- Paid Access: Since March 2023, Midjourney has fully switched to a paid model, with a minimum subscription of $10 per month, which may be expensive for beginner users.
- Usage Limitations: A Discord account is required, and for users in some countries, access is restricted due to regional limitations.
- Complex Interface: Beginners may find it difficult to navigate working through the Discord bot.
Fortunately, there are many apps like Midjourney that offer similar functionality and more user-friendly interfaces.
We will review seven of the best Midjourney alternatives. For all the AI networks considered, we will generate an image using the following prompt: “Generate an image of the Swiss Alps.”
Free Alternatives
First, let’s look at Midjourney alternatives that can be used for free.
Playground AI
Playground AI is an AI network that works on modern generative models, including Stable Diffusion XL, and allows generating images from text prompts or editing existing images.
A unique feature of Playground AI is the ability not only to generate an image from scratch but also to refine it within the same interface. Users can correct individual details, replace elements (for example, hands), perform upscaling to increase detail, or draw additional parts of the image on a special working field (canvas) with a seamless continuation of the image.
Using the free plan, users can generate up to 5 images every 3 hours.
Advantages:
- Work with a library of ready-made images and prompts, and the ability to copy and refine other users’ creations.
- Built-in canvas tool for extending and editing images while maintaining stylistic consistency.
- Support for multiple models.
Image generated by Playground AI using the prompt “Generate an image of the Swiss Alps”
Bing Image Creator
Bing Image Creator is an image generation tool from Microsoft, based on the latest version of OpenAI’s DALL·E model.
The service works using a diffusion architecture: the AI network analyzes the text prompt and synthesizes a unique image considering specified styles, details, emotions, backgrounds, and objects. Users can describe the desired image in any language, and the AI interprets the prompt to generate multiple options for selection.
Advantages:
- Completely free.
- Multiple image generation models to choose from.
- Integration with Microsoft ecosystem: Microsoft Copilot, Bing, Bing Chat, Microsoft Edge.
- Built-in content filtering and internal security algorithms to prevent illegal or inappropriate image generation.
Image generated by Bing Image Creator using the prompt “Generate an image of the Swiss Alps”
Paid Alternatives
Among the paid Midjourney alternatives, the following stand out.
Leonardo AI
Leonardo AI functions as a cloud platform for AI-based image generation. Its main function is creating high-quality visual materials from text descriptions.
Leonardo AI uses modern image generation algorithms similar to diffusion models, with additional innovative tools to improve quality and flexibility. Users can select from multiple artistic styles and genres, and also use the Image2Image feature to upload a reference image for more precise control. Users can adjust the “weight” of the generated image to balance between strict adherence to the reference and creative interpretation of the text.
Advantages:
- Free access with a limit (up to 150 tokens per day).
- Ability to train custom AI models.
- Wide choice of styles and customization tools.
- Support for generating textures and 3D objects.
- Convenient prompt handling: a built-in prompt generator helps beginners formulate queries, while experienced users can optimize prompts for better results.
Image generated by Leonardo AI using the prompt “Generate an image of the Swiss Alps”
Stable Diffusion
Stable Diffusion is a modern text-to-image generation model that uses diffusion model technology.
Developed by Stability AI in collaboration with researchers from LMU Munich and other organizations, the model was released in 2022 and quickly gained popularity due to its openness and high efficiency.
Stable Diffusion can be accessed through many services, including DreamStudio, Stable Diffusion Online, Tensor.Art, and InvokeAI.
Advantages:
- Multiple interfaces available.
- Flexible settings (Negative Prompt, aspect ratio, generation steps, fine-tuning, service integration, inpainting for parts of an image, outpainting for backgrounds).
- Numerous custom models (anime, realism, fantasy).
- Possibility of local deployment on powerful PCs.
- Open-source code. Unlike many proprietary models (DALL-E, Midjourney), Stable Diffusion can be run, trained, and modified locally.
Image generated by Stable Diffusion using the prompt “Generate an image of the Swiss Alps”
NightCafe
NightCafe is an online platform for generating images from text prompts and images. It uses multiple advanced algorithms and generation models, such as VQGAN+CLIP, DALL·E 2, Stable Diffusion, Neural Style Transfer, and Clip-Guided Diffusion. Users input a text prompt or upload an image, and the AI transforms it into a unique artistic work. Various styles, effects, resolution and detail settings, as well as editing and upscaling options, are available.
Advantages:
- Numerous options for customizing generated images, suitable for digital art, NFTs, and other purposes.
- Built-in functionality for modifying existing images via text prompts, scaling without quality loss, and object removal.
- Free access with limited generations.
- Support for multiple styles and algorithms.
- User-friendly interface.
Image generated by NightCafe using the prompt “Generate an image of the Swiss Alps”
Artbreeder
Artbreeder operates using generative adversarial networks (GANs). The main principle is creating new images by “crossing” or blending two or more images (“parents”), with fine control over parameters (“genes”) that determine various image traits. Users can interactively control the resulting image with sliders, adjusting characteristics like age, facial expression, body type, hair color, level of detail, and other visual elements.
Advantages:
- Interactive blending allows combining different images to create unique compositions, such as portraits, landscapes, or anime styles.
- Detailed manual adjustments of each image parameter (brightness, contrast, facial features, accessories, etc.) allow for highly refined results.
Image generated by Artbreeder using the prompt “Generate an image of the Swiss Alps”
Ideogram
Ideogram is a generative AI model specialized in creating images containing text. It uses advanced deep learning and diffusion algorithms.
Unlike many other AI visualization tools, Ideogram can generate clear, readable text within images, making it especially useful for designing logos, posters, advertisements, and other tasks where combining graphics and text is important.
Advantages:
- Free generations with selectable styles.
- Support for integrating readable and harmonious text into images—convenient for designers, marketing teams, and social media specialists.
- Built-in social platform with user profiles, sharing capabilities, and community interaction.
Image generated by Ideogram using the prompt “Generate an image of the Swiss Alps”
Conclusion
The choice of a Midjourney alternative depends on your goals and preferences: if you need the highest-quality image generation, consider Ideogram or Stable Diffusion 3. For free solutions, Leonardo AI and Playground AI are suitable, and if speed and simplicity are priorities, Bing Image Creator from Microsoft is a good option.
Each service has its own advantages, whether it is accessibility, detail quality, or flexibility of settings. It’s worth trying several options to find the best tool for your needs.
Infrastructure
11.09.2025
7 min read
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Infrastructure
VMware Cloud Director: What It Is and How to Use It
VMware Cloud Director (formerly vCloud Director, or “vCD”) is a modern solution for cloud providers, mainly designed for building virtual data centers on top of physical infrastructure. The platform allows combining all of a data center’s physical resources into virtual pools, which are then offered to end users on a rental basis.
It integrates tightly with VMware’s own technologies: vCenter and vSphere. vCenter is a set of tools for managing virtual infrastructure, and vSphere is the virtualization platform for cloud computing.
Key Capabilities of VMware Cloud Director
Creation of virtual data centers (vDCs) with full isolation of virtual services and resources.
Migration of virtual machines (VMs) between clouds, and self-deployment of OVF templates.
Snapshots and rollback of VM changes.
Creation of isolated and routable networks with external access.
Integrated, tiered storage with load balancing between virtual machines.
Network security: perimeter protection and firewalling.
Encryption of access to cloud resources to secure the virtual infrastructure.
Unified authentication across all VMware services (single sign-on) so users don’t need to re-authenticate.
Deployment of multi‑tier applications as ready-made virtual appliances, with VMs and OS images.
Allocation of isolated resources for different departments within a single virtual structure.
How VMware Cloud Director Works
VMware Cloud Director uses a multi-tenant model. Rather than building a dedicated environment for every customer, it creates a shared virtual environment. This reduces infrastructure maintenance costs massively: for large cloud providers, savings can reach hundreds of thousands or even millions of dollars per year, which in turn lowers the rental cost for end users.
Resource consumption model:
Using vCenter and vSphere, the provider aggregates physical resources into a shared pool called a “virtual data center” (vDC).
From that pool, resources are allocated into Org vDCs (Organizational Virtual Data Centers), which are the fundamental compute units consumed by customers.
VMware Cloud Director syncs with the vSphere database to request and allocate the required amount of resources.
Org vDCs are containers of VMs and can be configured independently. Customers can order different numbers of Org vDCs for different purposes, e.g., one Org vDC for marketing, another for finance, a third for HR. At the same time, interconnectivity can be established between these Org vDCs, forming a large, virtual private data center.
It’s also possible to combine Org vDCs into multiple networks. Additionally, within those networks, one can create vApps (virtual applications) made up of VMs, each with their own gateways to connect to Org vDCs. This setup allows building virtual networks of any architecture, isolated or routable, to match various business needs.
When such a network is created, the provider assigns a user from the customer organization to the role of network administrator. A unique URL is also assigned to each organization. The administrator is responsible for adding or removing users, assigning roles and resources, creating network services, and more. They also manage connections to services provided by the cloud provider. For instance, VM templates or OVF/OVA modules, which simplify backup and VM migration.
Resource Allocation Models in VMware Cloud Director
VMware Cloud Director supports several models for allocating resources, depending on how you want to manage usage:
Allocation Pool: You set resource limits and also define a guaranteed percentage of the shared pool for a user. This model is good when you want predictable costs but don’t need full reservation.
Pay-As-You-Go: No guaranteed resources, only consumption-based; ideal if usage is variable. The model is flexible and fits users who want to grow gradually.
Reservation Pool: You reserve all available resources; user requests are limited only by what the provider’s data center can supply. Reservation Pool is suited for organizations that need fixed performance and large infrastructure.
Useful Features of VMware Cloud Director
Here are several powerful features that optimize resource usage, routing, and tenant isolation:
Delegation of Privileges
You can assign network administrators from the users of each organization. These admins get broad rights: they can create and manage VMs, deploy OVF/OVA templates, manage VM migration, set up isolated/routable networks, balance VM workloads, and more.
Monitoring and Analytics
Cloud Director includes a unified system for monitoring and analyzing VM infrastructure: VMs, storage, networks, memory. All data is logged and visualized in a dedicated dashboard, making it easier to detect and resolve problems proactively.
Networking Features
Networking in vCloud Director supports dynamic routing, distributed firewalls, hybrid cloud integration, and flexible traffic distribution. Many of these features are now standard in the newer versions of Cloud Director. If you don’t already have some of them, you may need to upgrade your NSX Edge and convert it to an Advanced Gateway in the UI.
Dynamic routing improves reliability by eliminating manual route configuration. You can also define custom routing rules based on IP/MAC addresses or groups of servers. With NSX Edge load balancing, incoming traffic can be distributed evenly across pools of VMs selected by IP, improving scalability and performance.
Access Control and More
You can create custom user roles in the Cloud Director UI to control access tailored to organizational needs.
VMs can be pinned to specific ESXi host groups (affinity rules), which helps with licensing or performance. If Distributed Resource Scheduler (DRS) is supported, Cloud Director can automatically balance VMs across hosts based on load.
Additional useful features include automatic VM discovery and import, batch updating of server cluster cells, and network migration tools.
25 November 2025 · 5 min to read
Infrastructure
Why Developers Use the Cloud: Capabilities and Advantages
Today, up to 100% of startups begin operating based on providers offering services ranging from simple virtual hosting to dedicated servers. In this article, we will examine the advantages of cloud computing that have led to its dominance over the “classic” approach of having a dedicated server in a separate room.
Cloud Use Cases
Typical scenarios for using cloud technologies include:
Full migration of a business application to a remote server. For example, enterprise resource planning or accounting software. These applications support operation via remote desktop interfaces, thin clients, or web browsers.
Migration of specific business functions. Increasingly, archival copies are stored in the cloud while software continues running locally. Alternatively, a backup SQL server node can be hosted remotely and connected in case the local server fails.
Implementation of new services. Businesses are increasingly adopting automated systems for data collection and analytics. For example, Business Intelligence (BI) technologies have become popular, helping generate current and comparative reports.
Interaction between local and cloud environments. Hybrid services are well established in large networks. For example, a retail store may operate a local network with an on-site server, receive orders from an online store, and send requests back to transport companies, and so on.This setup allows offline operation even if the internet is fully disconnected: processing sales, receiving shipments, conducting inventories, with automatic synchronization once connectivity is restored.
These examples represent foundational scenarios, giving developers plenty of room to innovate. This is one reason more and more coders are attracted to the cloud.
Advantages
Now let’s examine the advantages and disadvantages of cloud computing. Yes, the technology has some drawbacks, including dependency on internet bandwidth and somewhat higher requirements for IT specialists. Experienced professionals may need retraining, whereas younger personnel who learn cloud technologies from the start do not face such challenges.
Speed
Software development often requires significant time and effort for application testing. Applications must be verified across multiple platforms, resolutions, and device types. Maintaining local machines dedicated to testing is inefficient.
Cloud computing solves this by enabling rapid deployment of virtually any environment, isolated from other projects, ensuring it does not interfere with team development. High deployment speed and access to cloud services also encourage IT startups to launch almost “from scratch,” with minimal resource investment.
The advantages of cloud services are especially critical when development volumes periodically expand. Purchasing hardware consumes a developer’s most valuable resource: time. In the cloud, selecting a plan takes just a few minutes, and the setup of a remote host for specific tasks can begin immediately. Hardware resources on the remote server, such as CPU cores, memory, and storage, can also be easily adjusted.
Security
Building a private server is expensive. Besides the powerful machines, you will need backup power and internet lines, a separate room with air conditioning and fire protection, and security personnel to prevent unauthorized access. Cloud providers automatically provide all these features at any service level.
Other security advantages include:
Easier identity and access management (IAM).
Higher reliability for continuous business operations.
Protection against theft or seizure of storage devices containing sensitive data.
On a cloud server, users cannot simply plug in a USB drive to download files. Data does not reside on local machines, and access is controlled according to company policy. Users only see what their role allows. This approach reduces the risk of viruses and accidental or intentional file deletion. Antivirus software runs on cloud platforms, and backups are automatically maintained.
Cost Efficiency
Purchasing server hardware is a major budget burden, even for large corporations. Before the cloud boom, this limited IT development. Modern developers often need test environments with unique infrastructure, which may only be required temporarily. Buying hardware for a one-time test is inefficient.
Short-term rental of cloud infrastructure allows developers to complete tasks without worrying about hardware maintenance. Equipment costs directly impact project pricing and developer competitiveness, so cloud adoption is advantageous. Today, most software is developed for cloud infrastructure, at least with support for it.
Maintenance, storage, and disposal costs for IT equipment also add up. Hardware becomes obsolete even if unused. This makes maintaining developer workstations for “simple” desktop software costly. Offloading this to a cloud provider allows developers to always work with the latest infrastructure.
Convenience
Another cloud advantage is ease of use. Cloud platforms simplify team collaboration and enable remote work. The platform is accessible from any device: desktop, laptop, tablet, or smartphone, allowing work from home, the office, or even a beach in Bali. Clouds have become a foundation for remote work, including project management.
Other conveniences include:
Easy client demonstrations: Developers can grant access and remotely show functionality, or run it on the client’s office computer without installing additional components.
Quick deployment of standard solutions: Setting up an additional workstation takes only a few minutes, from registering a new user to their trial login. New developers can quickly join ongoing tasks.
Easy role changes: In dynamic teams, personnel often switch between projects. Access to project folders can be revoked with a few clicks once a task is completed.
This also applies to routine work: adding new employees, blocking access for former staff, or reassigning personnel. A single administrative console provides an overview of activity and simplifies version tracking, archiving, and rapid deployment during failures.
Stability
Another factor affecting developer success is the speed of task completion. Beyond rapid deployment, system stability is critical. On local machines, specialists depend on hardware reliability. A failure could delay project timelines due to hardware replacement and configuration.
Moving software testing to the cloud enhances the stability of local IT resources, particularly in hybrid systems. Cloud data centers provide Tier 3 minimum reliability (99.982% uptime) without additional client investment. Resources are pre-provisioned and ready for use according to the chosen plan. Development, testing, and operation are typically conducted within a single provider’s platform, in an environment isolated from client services.
Conclusion
Cloud technologies offer numerous advantages with relatively few drawbacks. Businesses and individual users value these benefits, and developers are encouraged to follow trends and create new, in-demand products. Virtually all commerce has migrated to the cloud, and industrial sectors, especially those with extensive branch networks and remote facilities, are also adopting cloud solutions.
25 November 2025 · 6 min to read
Infrastructure
PostgreSQL vs MySQL: Which Database Is Right for Your Business?
PostgreSQL and MySQL are among the most popular relational databases. In this article, we will examine the functional differences between them and compare their performance so that you can choose the database that is suitable for your business.
PostgreSQL vs MySQL
Despite the increasing similarity in features between PostgreSQL and MySQL, important differences remain. For example, PostgreSQL is better suited for managing large and complex databases, while MySQL is optimal for website and online-application databases because it is oriented toward speed. This follows from the internal structure of these relational database systems, which we will examine.
Data Storage in PostgreSQL and MySQL
Like any other relational databases, these systems store data in tables. However, MySQL uses several storage engines for this, while PostgreSQL uses only a single storage engine. On one hand, this makes PostgreSQL more convenient, because MySQL’s engines read and write data to disk differently. On the other hand, MySQL offers greater flexibility in choosing a data engine.
However, PostgreSQL has an advantage: its storage engine implements table inheritance, where tables are represented as objects. As a result, operations are performed using object-oriented functions.
Support
The SQL standard is over 35 years old, and only the developers of PostgreSQL aim to bring their product into full compliance with the standard. The developers of MySQL use a different approach: if a certain feature simplifies working with the system, it will be implemented even if it does not fully conform to the standard. This makes MySQL more user-friendly compared to PostgreSQL.
In terms of community support, the number of MySQL developers still exceeds those working with PostgreSQL, but you can receive qualified help in both communities. In addition, many free guides and even books have been written about PostgreSQL, containing answers to most questions. It is also worth noting that both platforms are free, but MySQL has several commercial editions, which can sometimes lead to additional expenses.
Programming Languages
Both systems support a wide range of programming languages. Among the popular ones are C++, Java, Python, lua, and PHP. Therefore, a company’s development team will not face difficulties implementing features in either system.
Operating Systems
MySQL is a more universal system that runs on Windows, Linux, macOS, and several other operating systems. PostgreSQL was originally designed for Linux, but with the REST API interface, it becomes an equally universal solution that operates on any OS.
Data Processing
PostgreSQL provides more capabilities for data processing. For example, a cursor is used for moving through table data, and responses are written to the memory of the database server rather than the client, as in MySQL. PostgreSQL also allows building indexes simultaneously for several columns. It supports different index types, allowing work with multiple data types. This database also supports regular expressions in queries. However, new fields in PostgreSQL can only be added at the end of a table.
Parallel data processing is better organized in PostgreSQL because the platform has a built-in implementation of MVCC (multiversion concurrency control). MVCC can also be supported in MySQL, but only if InnoDB is used. Concerning replication, PostgreSQL supports logical, streaming, and bidirectional replication, while MySQL supports circular replication as well as master-master and master-standby. Replication refers to copying data between databases located on different servers.
PostgreSQL and MySQL: Performance Comparison
Testing is fair only when comparing two clean, “out-of-the-box” systems. Indexed testing provides the following results:
Insertion: PostgreSQL is more than 2.7× faster, processing a 400,000-record database in 5.5 seconds versus 15 seconds for MySQL.
Inner join: PostgreSQL processes 400,000 records in 1.1 seconds, MySQL in 2.8 seconds: a gain of more than 2.5×.
Indexed sorting: PostgreSQL processes the same number of records in 0.9 seconds, MySQL in 1.5 seconds.
Grouping: For the same 400,000-record database, PostgreSQL achieves 0.35 seconds, MySQL 0.52 seconds.
Indexed selection: PostgreSQL is 2× faster: 0.6 seconds vs. 1.2 seconds.
When it comes to updating data, PostgreSQL’s update time increases gradually as the number of records grows, while MySQL processes them in roughly the same time, starting from 100,000 records. This is due to different data-storage implementations. Nevertheless, PostgreSQL holds a significant advantage over MySQL even with large data volumes: 3.5 seconds versus 9.5 seconds for 400,000 records—more than 2.7× faster.
Without indexes, PostgreSQL also shows surprisingly high performance, processing a 400,000-record database in 1.3, 0.7, and 2.2 seconds for inner join, selection, and update operations, respectively.
Thus, PostgreSQL delivers an average performance advantage of about 2× (2.06). Although MySQL was originally positioned as a high-performance platform, constant optimization by the PostgreSQL development team has resulted in greater efficiency.
Advantages for Developers
Here we consider only the unique features characteristic of each platform. Therefore, we will not discuss support for MVCC or ACID, as these features are present in both systems.
From a developer’s perspective, MySQL is advantageous because it:
Provides increased flexibility and is easily scalable, with more than ten storage engines based on different data-storage algorithms.
Handles small read-oriented databases more efficiently (i.e., without frequent writes).
Is easier to manage and maintain, because it requires less configuration and fewer preparatory steps before starting work.
From a developer’s perspective, PostgreSQL is advantageous because it:
Offers an object-oriented approach to data, enabling inheritance and allowing the creation of more complex table structures that do not fit the traditional relational model.
Handles write-oriented databases better, including validation of written data.
Supports object-oriented programming features, enabling work with NoSQL-style data, including XML and JSON formats.
Can support databases without limitations on data volume. Some companies use PostgreSQL to run databases as large as several petabytes.
PostgreSQL and MySQL Comparison
For clarity, the main features of both systems can be presented in a table:
PostgreSQL
MySQL
Supported OS
Solaris, Windows, Linux, OS X, Unix, HP-UX
Solaris, Windows, Linux, OS X, FreeBSD
Use cases
Large databases with complex queries (e.g., Big Data)
Lighter databases (e.g., websites and applications)
Data types
Supports advanced data types, including arrays and hstore
Supports standard SQL data types
Table inheritance
Yes
No
Triggers
Supports triggers for a wide range of commands
Limited trigger support
Storage engines
Single (Storage Engine)
Multiple
As we can see, several features are implemented only in PostgreSQL. Both systems support ODBC, JDBC, CTE (common table expressions), declarative partitioning, GIS, SRS, window functions, and many other features.
Conclusion
Each system has its strengths. MySQL handles horizontal scaling well and is easier to configure and manage. However, if you expect database expansion or plan to work with different data types, it is better to consider implementing PostgreSQL in advance. Moreover, PostgreSQL is a fully free solution, so companies with limited budgets can use it without fear of unnecessary costs.
24 November 2025 · 6 min to read
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