Databases are increasingly managed services offered by cloud providers (AWS, Azure, GCP), simplifying scaling, maintenance, and global distribution. Businesses frequently adopt multi-cloud strategies for resilience and vendor lock-in avoidance. This is becoming increasingly relevant for businesses in Bangladesh, as cloud infrastructure becomes more accessible.
3. The Impact of Artificial Intelligence (AI):
AI-Driven Database Management: AI is revolutionizing database administration by automating tasks like performance tuning, anomaly detection, query optimization, and security patching. Autonomous databases are becoming a reality.
AI-Enhanced Data Analytics: AI and Machine Learning (ML) algorithms are integrated directly into databases for real-time analytics, predictive insights, and even natural language querying.
New Data Types for AI: The explosion of AI has driven the need for physician data specialized databases (like Vector databases) to store and query embeddings, enabling capabilities like semantic search and generative AI.
Data Quality and Governance: AI is being used to improve data quality, automate data cataloging, and enhance data governance, crucial for reliable AI models.
As IoT devices proliferate, data is increasingly generated at the "edge" – closer to the source. Special databases optimized for low-latency processing and smaller footprints are deployed at the edge, reducing reliance on centralized cloud systems and enabling real-time actions. This is particularly relevant in areas like smart agriculture or manufacturing in regions like Rajshahi.
5. Data Lakehouses and Unified Data Platforms:
The industry is moving towards unified data platforms (often called "data lakehouses") that combine the flexibility of data lakes (for raw, diverse data) with the structure and performance of data warehouses (for analytics), often leveraging various special databases as components within this ecosystem.