Choosing a database for a high-load project: SQL vs. NoSQL and hybrid solutions

The wrong database choice can cost a company millions of dollars. Twitter spent years rewriting its architecture because of MySQL's inability to handle the social network's load. Instagram, on the other hand, served a billion users on just a few PostgreSQL servers thanks to the right architecture. The difference between these scenarios lies in understanding the fundamental differences between the types of data stores and being able to map them to the actual requirements of the project.

The difference between these scenarios lies in understanding the fundamental differences between the types of data stores and being able to map them to the actual requirements of the project.

Architectural Features and Operating Principles

SQL databases: proven reliability

Relational databases are built on ACID (Atomicity, Consistency, Isolation, Durability) principles, which ensures a high level of data integrity. The structured SQL query language provides powerful tools for sophisticated analytics and ensures strict data typing.

The key benefits of SQL:

• Guaranteed data consistency
• Rich capabilities for complex queries and analytics
• Mature ecosystem of tools and experts
• Standardised query language

Restrictions:

• Vertical scaling with high cost
• Hard to horizontally distribute data across multiple servers
• Flexible data schema making fast iterations difficult

NoSQL: flexibility for the era of big data

NoSQL-systems follow the BASE principle (Basically Available, Soft state, Eventual consistency), sacrificing strict consistency for the sake of high availability and performance. There are four main types of NoSQL databases: document-oriented, key-value, columnar and graph.

Benefits of NoSQL:

• Horizontal scalability out-of-the-box
• Flexible data schema for rapid development
• High performance for specific usage scenarios
• Optimisation for specific data access patterns

Disadvantages​:

• Limited capabilities for complex queries
• Eventual consistency can complicate application logic
• Less mature ecosystem compared to SQL

Performance and scalability analysis

Vertical vs horizontal scaling

SQL databases traditionally rely on vertical scaling - increasing server capacity. PostgreSQL and MySQL can run efficiently on servers with 1TB+ RAM, but the cost of this approach grows exponentially. Modern solutions like PostgreSQL with clustering extensions (Citus) or MySQL Cluster can partially solve the horizontal scaling problem.

NoSQL systems were originally designed for horizontal scaling. MongoDB automatically distributes data to shards, Cassandra provides linear scalability, and Redis Cluster allows scaling in-memory operations to hundreds of nodes.

Load patterns and optimisation

For OLTP (Online Transaction Processing) systems with many small transactions, SQL databases often show excellent performance due to advanced query optimisers. For OLAP (Online Analytical Processing) scenarios, columnar NoSQL systems such as ClickHouse demonstrate multiple times better performance on analytical queries.

Global examples of applications

Successful SQL implementations

Netflix uses MySQL and PostgreSQL for critical metadata and billing, processing millions of transactions daily. The company uses a complex architecture with master-slave replication and custom sharding solutions.

Stripe built its payment platform on PostgreSQL, processing hundreds of billions of dollars a year. The use of ACID transactions is critical for financial transactions where any data loss is unacceptable.

NoSQL in the enterprise segment

Amazon uses DynamoDB (a proprietary NoSQL system) for its product catalogue, serving billions of queries per day. Eventual consistency achieves sub-millisecond latency at global scale.

Uber uses Cassandra to store geolocation data and ride history. The system processes petabytes of data with a 99.99% availability requirement.

Facebook (Meta) developed and uses RocksDB to store the social graph, serving 3+ billion active users with microsecond latencies.

Hybrid architectures: the best of both worlds

Polyglot Persistence

Modern high-load systems often adopt the Polyglot Persistence approach - using different database types for different tasks within a single project.

A typical architecture may include:

• PostgreSQL for transactional operations and metadata
• Redis for caching and user sessions
• Elasticsearch for full-text search
• ClickHouse for analytics and reporting
• S3/MinIO for file storage

NewSQL: evolution of traditional approaches

NewSQL systems like CockroachDB, TiDB and VoltDB attempt to combine the ACID guarantees of SQL with the horizontal scalability of NoSQL. These solutions show promising results, but require deep expertise for proper customisation.

Practical experience: cases from real projects

Moldova's largest marketplace: hybrid architecture in action

While developing the largest marketplace in Moldova, our team faced the classic challenges of high-load e-commerce systems: the need to provide instant catalogue search of 2+ million products, caching of user sessions for 100,000+ concurrent buyers and handling peak loads during sale periods.

The architectural solution included:

Redis as the primary caching solution showed impressive results:

• Response time for customer shopping cart requests reduced from 300ms to 15ms
• Session user data became instantly available
• System withstands peak loads of up to 50,000 RPS thanks to hot data caching
• Rate limiting implementation to protect against DDoS attacks via Redis Sliding Window

Elasticsearch has transformed the user experience of search:

• Automatic query completion works with less than 50ms latency
• Faceted search by category, brand and features is processed in 100ms
• Search with typos and synonyms increased conversion by 23%
• Full-text search by product descriptions indexes 5TB of text data
• Administrative dashboard with real-time analytics made possible by Elasticsearch aggregations

MySQL: a reliable foundation for 85% of our projects

In our practice, MySQL remains the primary DBMS for 85% of the projects we develop, and for good reason:

Technical maturity and reliability: MySQL 8.0 provides open source enterprise functionality. The decades-old query optimiser efficiently handles complex JOIN operations. Master-slave replication works stably even with terabyte data volumes.

Cost-effectiveness: No licence fees are critical for startups and medium-sized companies. A single MySQL server with 64GB RAM can handle a load that would require a cluster of 10+ nodes in some NoSQL solutions. The operational costs of administration are significantly lower.

Ecosystem and expertise: The market for MySQL specialists is much better developed than NoSQL alternatives. The average salary of a MySQL developer is 30% lower than a MongoDB expert with comparable performance for typical business tasks. Monitoring, backup and diagnostic tools are elaborated to the last detail.

Practical results in our projects:

• CRM system on MySQL processes 500,000 transactions per day with less than 100ms latency
• E-commerce platform scales to 1TB of data on a single master server
• Fintech application achieves 99.99% availability thanks to proven MySQL High Availability solutions
• MVP development time is reduced by 40% thanks to a familiar team ecosystem

When we move away from MySQL: Only under clear technical constraints: the need for horizontal sharding across hundreds of nodes, specific latency requirements (sub-millisecond responses), or when the data structure is fundamentally unsuited to the relational model.

Conclusion

Choosing a database for a highly loaded project is always a compromise between conflicting requirements. There is no one-size-fits-all solution for all scenarios. Success depends on a deep understanding of project specifics, workload patterns, and the available expertise of the team.

The key to making the right choice lies in careful requirements analysis, prototyping of critical scenarios, and a willingness to evolve the architecture as the system grows. Hybrid approaches often turn out to be the optimal solution, allowing you to utilise the strengths of different technologies.

Meta-Sistem is your reliable partner in designing and implementing high-loaded data management systems. Our team of experts has in-depth knowledge of SQL, NoSQL and hybrid architectures, helping clients to choose the best solution for their business.

We offer a full range of services, from auditing your current architecture and advising on technology selection to full development and support of highly loaded systems. Entrust your data architecture to Meta-Sistem professionals and get a solution that will scale with your business.