How to Choose Right Database?

Choosing the right database is crucial for any business. Let's find-out how to choose the right database for your needs.

How to Choose Right Database?
How to Choose Right Database?

Choosing the right database is a critical decision for any business or organization. Databases are essential for storing and managing large amounts of data, and choosing the wrong one can result in a slow and inefficient system. With so many database options available, it can be challenging to determine which one is the best fit for your needs.

In this article, we will provide guide on how to choose the right database. We will cover the different types of databases, their features, and how to evaluate which one is the best fit for your business. Whether you are starting a new project or considering switching to a new database, this guide will provide you with the knowledge you need to make an informed decision.

What is Database?

A database is a collection of organized data that is stored and managed using computer software. Databases are used to store and manage data for a wide variety of applications, from simple contact lists to complex enterprise-level systems.

Why Database is important for any Business?

Databases are essential tools for managing information related to their operations, customers, products, services, finances, and more. Databases allow businesses to organize and store data in a structured and efficient manner, making it easier to access, retrieve, and analyze information when needed.

In short, Databases are essential tools for any modern business that wants to stay competitive and agile in today's fast-paced business environment. They provide a secure, reliable, and scalable way to manage and store data, enabling businesses to make better decisions, optimize their operations, and deliver superior customer experiences.

Types of Databases

and Factors

How to Choose Right Database?, Types of Databases With Example
Types of Databases With Example

Consider These Factors:

  1. Data Model: Relational databases use a tabular data model, while non-relational databases use various data models such as document, key-value, or graph.
  2. Structure: Relational databases store data in rows and columns, while non-relational databases have a more flexible and hierarchical structure.
  3. Scalability: Relational databases can scale vertically and horizontally, while non-relational databases typically scale horizontally.
  4. Query Language: Relational databases use SQL, while non-relational databases often use a variety of NoSQL query languages.
  5. ACID Compliance: Relational databases are typically ACID compliant, while non-relational databases often sacrifice consistency for availability and partition tolerance (eventual consistency).
  6. Data Consistency: Relational databases typically have strong data consistency, while non-relational databases often have eventual consistency.
  7. Use Cases: Relational databases are commonly used for banking systems, HR management, and e-commerce platforms, while non-relational databases are popular for big data, IoT, and social networks.
  8. In-Memory Databases: Store data in memory, which allows for faster access times and high-speed transactions.
  9. Cloud Databases: Cloud-based databases that provide automatic scalability and management, often offering a variety of data models and query languages.
  10. ACID or BASE: In-memory databases and cloud databases may offer either ACID compliance or BASE (Basically Available, Soft state, Eventual consistency) depending on the use case.

Before we dive into the key considerations for choosing the right database, let's first look at the different types of databases available.

1. Relational Databases

Relational databases are the most commonly used type of database. They store data in tables with rows and columns, and the relationships between the tables are defined by primary and foreign keys. Relational databases are best suited for storing structured data and are ideal for transactional systems such as e-commerce platforms, banking systems, and inventory management systems.

2. Non-Relational Databases

Non-relational databases, also known as NoSQL databases, do not use tables to store data. Instead, they use other data models such as key-value pairs, documents, or graphs. Non-relational databases are best suited for storing unstructured data and are ideal for big data applications, social media platforms, and content management systems.

3. In-Memory Databases

In-memory databases store data in memory instead of on disk, which provides faster access times and better performance. In-memory databases are best suited for applications that require real-time data processing, such as financial trading platforms and real-time analytics systems.

4. Cloud Databases

Cloud databases are hosted and managed by cloud service providers such as Amazon Web Services, Microsoft Azure, and Google Cloud Platform. Cloud databases provide scalability, high availability, and ease of management, making them an ideal choice for applications that require high availability and scalability.

Important Factors for Database to Consider

1. Scalability:

Scalability is a critical consideration when choosing a database. You need to consider whether the database can handle the growth of your data over time. Relational databases can handle a limited amount of data, whereas non-relational databases can handle large amounts of unstructured data. In-memory databases are ideal for real-time applications that require fast access to data.

2. Data Structure:

The structure of your data will also determine the type of database you should choose. Relational databases are best suited for structured data with predefined relationships, whereas non-relational databases are best suited for unstructured data with varying relationships.

3. Performance:

Performance is a crucial consideration when choosing a database. You need to consider how quickly the database can process queries and retrieve data. In-memory databases provide the fastest performance, followed by non-relational databases and relational databases.

4. Security:

Security is another important consideration when choosing a database. You need to ensure that your data is protected from unauthorized access, and the database you choose should have robust security features such as encryption, access controls, and authentication mechanisms.

5. Cost:

Cost is another important factor when choosing a database. The cost of a database can vary significantly depending on the type of database, the hosting options, and the licensing terms. You need to consider both the upfront costs and ongoing maintenance costs when evaluating the total cost of ownership.

6. Ease of Use:

Ease of use is another important consideration, especially if you are new to databases. You need to choose a database that is easy to set up, configure, and manage. Relational databases have a more structured approach to data management, whereas non-relational databases provide more flexibility but can be more complex to manage.

7. Support and Community:

Finally, you need to consider the level of support and community around the database. You want to choose a database that has an active community of users and developers who can provide support, share best practices, and help troubleshoot issues

Choosing the Right Database

for a Highly Scalable System

When it comes to building a highly scalable system, choosing the right database is undoubtedly the most crucial decision we'll ever make. If we're tasked with the challenge of picking the next database for our rapidly growing business, we must consider several key points. We are talking about a database for a growing business where a wrong choice could lead to extended downtime, customer impact, and even data loss. We're not picking something for our weekend project.

Before making any decision, we need to consider if we need a different database. Is there a compelling reason to look for an alternative? Is the existing database breaking at the seams? Maybe the p95 latency is through the roof, or perhaps the working set is overflowing the available memory, and even the most basic requests need to go to the disk, slowing everything down.

We need to ensure that these issues are not easily solvable. We should read the database manual of our current database system, from front to back, and read it again. There could be a configuration knob or two that we can tweak to give us a bit more breathing room. This breathing room could come in handy because migrating a database could take a long time, usually much longer than we think. These knobs could come in the form of tuning the working set memory size, choosing a different compaction strategy, or even changing some garbage collection behavior.

Databases are complex and highly tunable. We must understand the architecture of our database, know its limitations, and reach out to experts in the community. People in the know could help, and often in surprising ways.

To look for more untapped headroom, perhaps there are some fixes to our application architecture that would give us more breathing room. Can we put a cache in front of it and give us a few more months of runway? Can we add read replicas to offload some read load? Can we shard the database or partition the data in some way? Maybe the data is naturally siloed, and sharding is an acceptable solution.

The bottom line is that migrating a live production database is risky and costly. We must be sure that there is no way to keep using the current database before considering a switch.

Choosing the next database is not an easy task, and we should not be swayed by marketing claims. We should prefer the databases that have been around for a long time and have been battle-tested. Depending on the industry we are in, our posture could be a little different. Banking and finance, for example, are more conservative. Whatever it is, there should be a ready market of experienced administrators and developers for the database we are considering.

When it comes to databases, there is no free lunch. We must be wary of outrageous marketing claims. Infinite, effortless horizontal scalability comes with a hidden cost. We must dig deep to find where that cost is hiding. Instead of reading the shiny brochures, we should read the manual. There is usually a page called "Limits," and that page is a gem. The FAQ section is also very useful. These pages in the manual are where we learn the real limits of a new database. Its design constraints - the fine prints, so to speak.

For example, many NoSQL databases support much higher scales than the trusty old relational databases. They often claim to support near-linear horizontal scalability. However, these databases often eliminate or limit transactional guarantees and severely limit data modeling flexibility. There are no queries across data entities, and the data is highly denormalized, where the same piece of data is stored in many collections to support different data access patterns.

To learn more about a particular database, one can join the chat room and ask lots of questions. For open-source projects, reading GitHub issues can also be helpful. It's important to invest time in researching the candidate databases before making a decision.

Once the database options have been narrowed down, it's time to create a realistic test bench for the candidates using our own data and real-world access patterns. Although this can be costly and time-consuming, it's essential to avoid the risks and costs associated with migrating a production database. During benchmarking, it's important to pay attention to outliers and measure P99 of everything, as the average is not always meaningful. Replicating the real workload and testing risky operational tasks, such as failing over a node or testing for data corruption during network partitions, can help determine where the database starts to break.

After the database has been thoroughly tested and checked, it's time to plan the migration carefully. A detailed step-by-step migration plan should be written out and reviewed by peers. If possible, migrate a small service first to learn as much as possible before fully committing to the migration. Picking the right database can be a lot of hard work, but it's worth it in the end.

Conclusion

In summary, selecting the right database for your business is a complex process that requires careful consideration of multiple factors. However, by taking the time to evaluate your requirements and researching different options, you can find a database that meets your needs and helps you achieve your business goals.

When choosing a database, it's important to prioritize your specific needs and goals over any industry hype or buzz. Don't simply go for the most popular database or the one that is currently in vogue - instead, focus on the features and capabilities that matter most to your business.

It's also a good idea to consult with experts in the field, whether they are in-house IT professionals or external consultants. These experts can help you evaluate different database options and make informed decisions that align with your business objectives.

Overall, choosing the right database requires a strategic approach that takes into account a range of factors, including scalability, data structure, performance, security, cost, ease of use, and support. By carefully weighing these factors and making informed decisions, you can find a database that meets your needs and helps you achieve your business goals in the long term.

FAQs

What is a database?

A database is a collection of data that is organized and stored in a way that makes it easy to access, manage, and update.

What are some common types of databases?

Some common types of databases include relational databases, document databases, key-value databases, and graph databases.

What is the difference between a relational database and a non-relational database?

Relational databases store data in tables with predefined relationships, whereas non-relational databases use other data models such as key-value pairs, documents, or graphs.

What is the difference between a SQL and NoSQL database?

SQL databases use structured query language to manage data in a table format, while NoSQL databases are designed to handle unstructured data and use a variety of data models.

What is an in-memory database?

In-memory databases store data in memory instead of on disk, which provides faster access times and better performance.

What is a cloud database?

A cloud database is hosted and managed by cloud service providers such as Amazon Web Services, Microsoft Azure, and Google Cloud Platform.

What is database performance?

Database performance refers to the speed and responsiveness of a database when handling queries and transactions.

What is database scalability?

Database scalability refers to the ability of a database to handle increasing amounts of data and traffic without sacrificing performance.


Reference headlines for this post:

  1. Understanding Relational Databases: A Beginner's Guide
  2. What Are Non-Relational Databases and How to Choose One?
  3. SQL Databases: What You Need to Know Before Choosing One
  4. Choosing the Right NoSQL Database for Your Application
  5. How to Choose a Scalable Database Solution for Your Business
  6. How to Evaluate Database Performance and Choose the Right One
  7. How to Choose a Secure Database for Your Business
  8. How to Choose a Database with Reliable Backup and Recovery
  9. Choosing a Google Cloud Database for Your Business
  10. WS Database Options: Which One is Right for Your Business?

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