The Rise of Modern Databases with AI/ML
Revolutionizing Data Management: AI/ML's Transformative Impact on Modern Databases
With the rise of the Modern tech stack and AI/ML, unstructured data generation and usage has been significantly increased. This journey has led to a huge database transformation, which doesn’t stop with simple row and column stores.
Modern businesses = Modern Databases
So, What are modern databases?
Imagine a business like a growing tree – as it gets bigger, it needs more room and more nutrients, more water. Similarly, as businesses grow and change, especially with all the digital stuff happening, they need databases that can keep up with all that growth and change.
Traditional databases are like old-school filing cabinets :) —they're good at what they do, but they have limits. Now, with so many people shopping online, sharing pictures, or chatting, there's just way more stuff to keep track of. That's where modern databases come in.
They're like super-smart filing systems that can grow really big and handle all kinds of information, even things like tweets or Instagram posts, not just neat and tidy rows of numbers.
Also, businesses aren't just in one place anymore. They're all over the internet, using the cloud. Modern databases are great at this because they can work across many places at once, keeping everything organized and running smoothly, no matter where the data or the users are. This is super important because it helps businesses understand their customers better, manage all their information more easily, and save money while they're at it.
Read more about: Database Landscape" What Are the Different Types of Databases? (Part-1) : https://www.databytego.com/p/database-landscape-what-are-the-different
(Optional read)Market insights : Database Trends
https://db-engines.com/en/ranking_trend
Let’s talk about what modern business need from modern database.
Key Features of Modern Databases:
Please remember that not necessary all the business or companies will required all the 8 elements of features. Every use case is unique and also each application needs is different.
1. Scalability: Enterprises today face an unprecedented volume of data. Modern databases are designed for scalability, enabling businesses to manage large and growing datasets effectively. They can handle the increased workload by distributing it across multiple database instances, which is a challenge for traditional relational databases.
2. Performance: High performance is a critical requirement. This includes quick data processing capabilities and the ability to handle complex queries efficiently. The performance tuning feature of Database Management Systems (DBMS) plays a vital role here, optimizing SQL queries and reducing I/O usage to deliver the best performance.
3. Security and compliance: With the handling of mission-critical and sensitive data, robust security features are non-negotiable. Modern databases provide advanced security measures, including strong authentication and authorization configurations, data encryption, and compliance with regulatory requirements.
4. High Availability and Reliability: Databases must ensure minimal downtime and data loss. That’s where PRO and PRT come into the picture. Features like data replication, automatic failover, and robust backup and recovery processes contribute to high availability.
5. Flexibility and Variety of Data: Modern enterprises generate various data types. The shift towards NoSQL databases caters to this diversity, allowing the storage and management of different forms of data, including unstructured and semi-structured data.
6. Reduced Complexity and Cost: Modern databases offer solutions to reduce the complexity of data management and operational costs. This includes the ability to integrate with cloud services and utilize data lakes for more efficient data storage and management.
7. Polyglot Persistence: A trend in modern database architecture is using multiple database systems within a single application to leverage the strengths of various database models. This approach allows using the right database technology for specific use cases.
So, How do I find the most suitable database for my application stack?
What is the nature and volume of your data?
Is your data structured, semi-structured, or unstructured?
Do you expect a significant increase in data volume?
What are your performance and scalability needs?
Do you require real-time data processing and analytics?
How important is the speed of read and write operations for your use case?
What kind of data consistency and reliability do you need?
Do you require strong consistency, or can you work with eventual consistency?
How critical is data accuracy and integrity for your application?
What are your backup and disaster recovery requirements?
What are your application's availability requirements?
Does your application need to be available without interruptions?
How do you plan to handle downtime or data center failures?
Is geographic distribution of data important for your use case?
What is your budget and resource availability?
What are your budget constraints for database management and maintenance?
Do you have the in-house expertise to manage certain types of databases?
Are you looking for a managed service or do you prefer managing the database on your own?
And if you are more like a visual person like me, this might be helpful.
Please feel free to read my blogs related to Data
Vector database and why it's Popular in AI
Database Landscape" What Are the Different Types of Databases? (Part-1)
The Importance of Data Governance and Data Security in Modern Organizations