Challenges in Creating Horizontally Scalable RDBMS Databases

RDBMS (Relational Database Management Systems) and NoSQL databases serve different purposes in today's data-driven environment. While NoSQL databases are increasingly popular due to their scalability and performance, creating horizontally scalable RDBMS databases remains a significant challenge. This article explores the inherent difficulties and the reasons behind this gap.

1. ACID Compliance and Consistency Challenges

ACID Properties

RDBMSs are designed to ensure the ACID (Atomicity, Consistency, Isolation, Durability) properties. These properties guarantee that every database transaction maintains the integrity of the data, making RDBMS a reliable choice for mission-critical applications. However, ensuring these properties across distributed systems is inherently more challenging than with single-server databases.

Consistency Challenges

Maintaining strong consistency across multiple nodes in a horizontally scaled environment leads to performance bottlenecks and increased complexity. Consistency requirements are particularly stringent in RDBMS, which can result in significant overhead and performance trade-offs when scaling horizontally.

2. Schema and Relationships

Fixed Schema

RDBMSs typically have a fixed schema, which can complicate horizontal scaling. Changes to the schema require coordinated updates across all instances, leading to significant downtime and operational complexity. This is in stark contrast to NoSQL databases, which can be more flexible in terms of schema management.

Complex Joins: RDBMSs often rely on complex joins between tables. Effectively distributing these tables across different nodes can lead to performance issues and complicate query performance.

3. Data Distribution

Sharding Complexity

Sharding can be implemented in RDBMSs to distribute data across multiple nodes, but it requires careful planning. The distribution of data must consider access patterns and relationships, leading to uneven load distribution and operational overhead.

Cross-Shard Transactions

Transactions that span multiple shards can be complex and inefficient, often requiring distributed transaction protocols like Two-Phase Commit, which add significant overhead. Ensuring consistency and reliability in cross-shard transactions is a major challenge in horizontally scaling RDBMS.

4. Scaling Challenges

Vertical vs. Horizontal Scaling

Traditional RDBMSs are often optimized for vertical scaling, adding more resources to a single server. While horizontal scaling is possible, it is not as seamless or straightforward as with many NoSQL solutions. The complexity of managing multiple nodes and ensuring consistency adds significant challenges.

Performance Bottlenecks

As the number of nodes increases, managing connections, queries, and transactions can lead to performance bottlenecks. Scaling out to handle large datasets and high volumes of queries requires sophisticated architectures and careful planning.

5. Design Philosophy and Use Cases

The design philosophy of RDBMSs and NoSQL databases diverges significantly. RDBMSs prioritize data integrity and relationships, making them less suitable for high-scalability and performance requirements. In contrast, NoSQL databases are designed for high availability, scalability, and flexibility, often at the expense of strict consistency.

Eventual Consistency

Many NoSQL databases embrace eventual consistency, allowing for greater scalability and performance at the cost of immediate consistency, which is often non-negotiable in RDBMS. Eventual consistency can be a viable trade-off in certain scenarios, but it may not be suitable for all use cases.

Conclusion

While there are efforts to create horizontally scalable RDBMS solutions (e.g., Google Spanner, CockroachDB), these solutions often involve trade-offs and complexities that NoSQL databases can avoid by relaxing consistency requirements and allowing for more flexible data models. As a result, RDBMSs are generally less suited for horizontal scaling compared to NoSQL alternatives, which are designed with scalability as a primary goal.