Serverless Database Options: Exploring NoSQL and NewSQL Solutions

Databases are the unsung heroes of our digital lives, quietly powering everything from your favorite social media to critical healthcare systems.

But the database field is undergoing a fundamental rethinking of how we store and access data. Designed for the cloud, these databases offer unprecedented flexibility and cost savings.

ScaleGrid's 2019 report revealed that while SQL databases still dominate the cloud with a 60% share, NoSQL databases are making significant inroads at 24%. That is a sign of a broader transformation in the tech industry.

Serverless databases are simplifying the complex chore of data management, eliminating the need for server upkeep and allowing developers to focus solely on crafting quality applications.

In this post, we'll dig deep into the technical details of NoSQL and NewSQL Serverless Databases, which are revolutionizing the way we think about data management.

Ready to dive deeper?

Let's get into the nuts and bolts of NoSQL and NewSQL Serverless Databases.

NoSQL Databases: Features, Pros, and Cons

NoSQL databases are a significant shift from the SQL databases we're accustomed to. Unlike their SQL counterparts, which require a fixed schema and emphasize ACID compliance, NoSQL databases offer a more flexible approach to data management. 

The variety in types of NoSQL databases is one of the strong suits of NoSQL and NewSQL Serverless Databases.

Here's a breakdown of the types:

NoSQL Database Advantages and Disadvantages

The advantages and disadvantages of NoSQL databases are crucial to understand when considering NoSQL and NewSQL Serverless Databases for your project. Let’s start with the advantages. 

Advantages of NoSQL

• Scalability: Features of NoSQL databases really shine when it comes to growing your business. You can easily add more servers whenever you need, instead of having to overhaul a single, central server. This is known as elasticity and is particularly useful for businesses that experience variable workloads.
• Flexible Schema: With traditional SQL databases, you have to define a schema before you can start adding data. But NoSQL databases let you add new fields as you go. This flexibility is especially useful when you're working with diverse data types, such as user comments or reviews.
• High Availability: NoSQL databases are built for resilience. If a server or data center fails, databases like Cassandra have built-in replication strategies to ensure data is not lost, and service can continue without interruption.
• Handling Unstructured Data: NoSQL databases excel at storing unstructured data, like social media posts, sensor data, or even complex nested data like user-generated reviews with multiple sub-comments.

Disadvantages of NoSQL Databases

• Lack of Standardization: NoSQL databases are not as standardized as relational databases, which means that each NoSQL database system may have its query language and data modeling approach. This lack of standardization can lead to a steeper learning curve for developers and administrators.
• Limited ACID Compliance: NoSQL databases often sacrifice full ACID (Atomicity, Consistency, Isolation, Durability) compliance in favor of performance and scalability. This can lead to data consistency issues in certain scenarios, making NoSQL databases less suitable for applications that require strong transactional guarantees.
• Limited Query Capabilities: NoSQL databases are generally designed for specific use cases and may not support complex queries as well as relational databases. This limitation can be a drawback for applications that require advanced querying and reporting capabilities.
• Data Integrity Challenges: Without the rigid schema enforcement of relational databases, NoSQL databases can be prone to data integrity issues. Inconsistent or incomplete data can be stored in the database, making it challenging to maintain data quality.
• Limited Joins: NoSQL databases typically do not support complex joins between tables like relational databases do. This can make it difficult to retrieve and combine data from multiple sources, requiring developers to perform these operations programmatically.

Popular NoSQL Databases

Popular NoSQL databases like Amazon DynamoDB and MongoDB Atlas are often used in NoSQL and NewSQL Serverless Database architectures. Primary ones include: 

• Amazon DynamoDB: DynamoDB is a NoSQL database service provided by Amazon Web Services (AWS). It's designed to offer seamless scalability and is fully managed, meaning AWS takes care of the operational burden. This makes it a popular choice for businesses that want to focus on application logic rather than database management.
• MongoDB Atlas: This is the cloud version of MongoDB, a leading document-based NoSQL database. MongoDB Atlas excels in storing JSON-like documents and offers a flexible, intuitive approach to data organization. It's particularly well-suited for startups and enterprises that deal with complex data types.
• Google Cloud Firestore: Firestore is a NoSQL document database within the Google Cloud Platform. Its standout feature is real-time data syncing. This is particularly beneficial for mobile apps that need to keep data updated across multiple devices in real-time.
• Azure Cosmos DB: This is Microsoft's entry into the NoSQL database arena. Cosmos DB is multi-model, meaning it can function as a document, key-value, wide-column, or graph database. This versatility makes it a strong choice for businesses with diverse data storage needs.

Considerations and Limitations

When opting for NoSQL and NewSQL Serverless Databases, it's important to consider the limitations of NoSQL databases. While there are plenty of limitations, most can be resolved easily except two. 

1. Lack of Standard Query Language: NoSQL databases don't have a one-size-fits-all query language. Each one has its unique querying methods, which can be a hurdle for developers unfamiliar with that specific system. So, choosing a NoSQL database is a significant decision. They excel in certain situations like handling big data or fast development cycles but may not be suitable for systems needing complex queries.
2. Consistency Models: Many NoSQL databases rely on an eventual consistency model. This means that, given no further updates to a specific data item, all future retrievals of that item will yield a consistent value. However, this model needs to be revised for applications requiring immediate consistency.

The decision to adopt a NoSQL database is significant. These databases have strengths in specific areas, such as handling large data volumes or accelerating development cycles. Yet, they may not be suitable for systems requiring intricate queries or transactions.

NewSQL Databases: Features, Pros, and Cons

Now that we've covered NoSQL, let's move on to the features of NewSQL in the context of NoSQL and NewSQL Serverless Databases. 

NewSQL databases are an innovative development in the field of database management systems. They ingeniously combine the strong consistency and ACID compliance of traditional SQL databases with the scalability and flexibility of NoSQL databases. 

This fusion creates a robust database system capable of supporting modern applications that demand both high transaction rates and unwavering data integrity. In essence, NewSQL databases are designed to meet the complex requirements of today's high-velocity, data-intensive applications.

NewSQL Databases Advantages

The advantages of NewSQL databases make them a compelling option within the broader category of NoSQL and NewSQL Serverless Databases.

• ACID Transactions: NewSQL databases uphold the principles of ACID (Atomicity, Consistency, Isolation, Durability) transactions. In applications where data integrity is crucial—like in financial or e-commerce systems—ACID compliance is essential. This ensures that database operations are executed reliably and without errors.
• Strong Consistency: NewSQL databases offer something many NoSQL databases don't – strong consistency. Once a transaction is finalized, the data is instantly consistent across the entire database. This is essential for apps that need real-time data accuracy, like inventory management systems.
• Horizontal Scalability and Sharding: NewSQL databases excel in horizontal scalability. They can distribute data across multiple servers or clusters, allowing for efficient data management as the system grows. This is achieved through sharding, a technique that breaks larger databases into smaller, more manageable pieces, thereby enhancing performance.
• High Performance for Complex Queries: NewSQL databases are designed for quick data retrieval and manipulation. They can handle intricate SQL queries more efficiently than many traditional SQL databases, making them a good fit for real-time analytics and data-heavy apps.

Prominent NewSQL Databases Examples

Examples like Google Cloud Spanner and CockroachDB are leading the way in the NewSQL segment of NoSQL and NewSQL Serverless Databases. An exploration of each is given below. 

• CockroachDB: This NewSQL database is highly regarded for its strong consistency and horizontal scalability features. It's engineered to provide fault tolerance, ensuring that your data remains accessible even in the event of hardware failures.
• Google Cloud Spanner: Spanner is unique for its global distribution capabilities. It offers strong consistency across multiple regions, making it an excellent choice for multinational corporations that require a unified, globally accessible database.
• NuoDB: NuoDB offers the familiarity of SQL queries while also providing the benefits of cloud-native scalability. It's particularly useful for businesses transitioning from traditional SQL databases but needing more flexibility and scalability.
• YugaByte DB: This database is engineered for peak performance. High throughput means it's capable of handling numerous operations every second. Low latency ensures that these operations are executed almost instantaneously. For applications that demand immediate data access, such as real-time analytics systems, YugaByte DB is an excellent option.

Key Considerations

When choosing between NoSQL and NewSQL Serverless Databases, several key considerations come into play

• The Scalability-Consistency: NewSQL databases offer both scalability and consistency. However, achieving one often requires sacrificing some degree of the other. This is a critical factor for organizations that require both uninterrupted service and data accuracy.
• Global Distribution: Certain NewSQL databases provide the option for multi-region data distribution. While this may seem advantageous, it introduces additional complexities in operations and could lead to increased costs. Businesses should assess whether global distribution aligns with their operational needs before opting for it

Furthermore, specific Use Cases: NewSQL databases aren't a catch-all solution. They're particularly good for environments that have a lot of transactions happening all the time or applications that need to run complex queries without sacrificing data integrity. 

So, before you choose a NewSQL database, you really need to understand what your specific application requires

Comparing NoSQL and NewSQL: When to Choose Which 

The choice between NoSQL and NewSQL in a serverless database environment depends on various factors. However, here are the four core factors that can be enough to make a choice.

Scalability and Performance

NoSQL databases often have an edge when it comes to scalability. They're designed to scale out, distributing data across multiple servers or nodes. This makes them a go-to for applications that need to handle massive amounts of data or user loads. 

On the flip side, NewSQL databases also offer horizontal scalability but add the benefit of strong consistency. If your application needs to scale but can't compromise on data integrity, a NewSQL serverless database might be the better fit.

Data Modeling and Flexibility

NoSQL databases offer a more flexible schema, making them suitable for unstructured or semi-structured data. They excel in scenarios where the data model is evolving rapidly. NewSQL databases, however, bring the best of both worlds. 

They offer the schema flexibility found in NoSQL databases while also providing the structured query capabilities of traditional SQL databases. So, if you're dealing with a mix of structured and dynamic data, NewSQL databases could be your best bet.

Consistency and Transactions

NoSQL databases often provide eventual consistency, which means they prioritize performance over immediate data accuracy. For some applications, this might be okay. But it's a no-go for systems that need data to be consistent in real-time. NewSQL databases provide strong consistency and are fully ACID-compliant, which makes them a solid choice for apps that need immediate data accuracy, like financial systems.

Use Cases and Industry Examples

Different industries have different needs, and NoSQL and NewSQL Serverless Databases cater to a wide range of use cases. NoSQL databases find frequent use in big data initiatives, content management systems, and real-time analytics. They are often the preferred choice for organizations requiring quick, scalable database solutions.

NewSQL databases, on the other hand, are making waves in sectors that require both scalability and strong consistency. You'll find them in high-transaction environments like e-commerce platforms and financial systems where data integrity can't be compromised.

Factors Influencing the Choice

Application Requirements

The choice between a NoSQL and a NewSQL serverless database often hinges on your project's specific needs. If you're dealing with complex, unstructured data and need the ability to make quick changes, a serverless NoSQL database could be your best bet. But if you need strong consistency, ACID transactions, and the ability to run complex queries, a serverless NewSQL database is likely a better fit. 

Keep in mind the performance expectations and the types of queries your app will mainly use. Always consider the performance expectations and the types of queries your application will predominantly use.

Cloud Provider Integration

The cloud provider you choose can also influence your decision to go with NoSQL and NewSQL Serverless Databases. AWS, GCP, and Azure each offer various database services that are easier to integrate within their own ecosystems. 

For instance, if you're already invested in AWS, Amazon DynamoDB (a popular NoSQL database) or Amazon Aurora (compatible with NewSQL) could be more convenient options. Ease of management and integration should be high on your list of considerations.

Cost Considerations

Budgeting is crucial when considering NoSQL and NewSQL Serverless Databases for your project. NoSQL databases like MongoDB Atlas often offer a more flexible pricing model, allowing you to pay as you go. 

NewSQL databases, however, may come with licensing fees and could be more expensive to scale. Always weigh the cost implications of both types of databases, including not just the upfront costs but also the long-term expenses associated with scaling and storage.

Conclusion

NoSQL and NewSQL Serverless Databases each have their unique strengths and weaknesses. Navigating the maze of database options can be daunting, but understanding the nuances between NoSQL and NewSQL serverless databases can make your decision easier. NoSQL databases offer scalability and flexibility, making them ideal for applications that handle a variety of data types and require quick adjustments. On the other hand, NewSQL serverless databases provide strong consistency and ACID compliance that certain applications can't do without.

Choosing between NoSQL and NewSQL Serverless Databases will ultimately depend on your specific needs and the challenges you face. Whether it's data complexity, query patterns, or performance expectations, evaluating these elements is crucial.

If you're still unsure, F22 Labs can help you decide about NoSQL and NewSQL Serverless Databases. Book a 1-hour free consultation and optimize your serverless architecture services. Click here to book and learn more.