Databases

Hi.

• AI-Driven & Autonomous Databases: Artificial intelligence and machine learning are being integrated into database management systems (DBMS) to automate routine tasks such as performance tuning, security patching, and anomaly detection. This leads to "self-driving" or autonomous databases (like Oracle Autonomous Database) that optimize operations with minimal human intervention, freeing up DBAs for more strategic work.
• Vector Databases for AI Workloads: The explosive growth of generative AI (GenAI) and large language models (LLMs) has driven the rise of vector databases (e.g., Pinecone, Weaviate, Milvus). These databases are purpose-built for storing and efficiently querying high-dimensional vector embeddings, which are crucial for applications like semantic search and AI-powered recommendation engines.
• Cloud-Native and Serverless Architectures: The adoption of cloud-native and serverless databases continues to grow rapidly. These models offer automatic scalability, high availability, and a pay-as-you-go pricing structure, which significantly reduces operational overhead and the need for infrastructure management, making them ideal for modern, agile applications.
• Multi-Model Databases: To manage diverse data types (relational, document, graph, key-value, time-series, and now vector data) within a single, integrated platform, multi-model databases are becoming more popular. This approach simplifies data management and eliminates the need for multiple, specialized databases, enabling greater flexibility and faster development cycles.
• Real-Time Analytics & Stream Processing: Businesses increasingly need instant insights to make quick decisions (e.g., fraud detection, dynamic pricing). This has fueled the demand for databases designed for real-time data processing and integration with stream processing platforms like Apache Kafka.
• Edge Computing and Distributed Databases: The proliferation of IoT devices and the need for lower latency are driving a shift towards edge computing, where data is processed closer to its source. Distributed databases (e.g., CockroachDB, Apache Cassandra) play a vital role here, ensuring data is available and processed quickly across multiple locations.
• Data Governance, Security, and Observability: With increasing data privacy regulations (like GDPR and CCPA), there is a strong emphasis on robust security measures and compliance. Trends include enhanced encryption, zero-trust architectures, and data observability platforms that monitor data quality, lineage, and health in real-time to ensure trust and compliance.
• Data Mesh and Data Fabric Architectures: To overcome the challenges of monolithic data warehouses and data silos, organizations are exploring modern data architectures like data mesh and data fabric. These approaches decentralize data ownership to domain-specific teams (data mesh) or use metadata to virtually connect disparate data sources (data fabric), improving agility and accessibility.
• PostgreSQL Renaissance: Open-source databases, particularly PostgreSQL, are experiencing a surge in popularity due to their flexibility, robust feature set, and strong community support. The addition of powerful extensions, such as for AI workloads and TimescaleDB for time-series data, makes it a highly relevant option for modern applications.

hi.

• Access to E-Journals: The university subscribes to a vast collection of national and international e-journals of repute.
• Online Databases: Students and faculty have access to standard professional databases. Examples of subscribed databases include:
  • SCOPUS
  • J-GATE  (including Engineering, Technology, Social & Management Science collections)
  • EBSCO HOST
  • Knowledge Hub
  • ClinicalKey
  • SciFinder Scholar
• Remote Access: The library facilities provide remote access to e-resources, meaning students and faculty can often access these journals and databases from anywhere, not just on campus.
• Physical Resources: In addition to e-resources, the library has an extensive collection of over 20,000 physical books, print journals, magazines, newspapers, theses, and research reports.
• Digital Infrastructure: The library uses modern software (e.g., DPU-ERP library software) with facilities like an Online Public Access Catalogue (OPAC) for data searches, Wi-Fi connectivity, and smart e-terminals.

 Chandigarh University ensures that biotechnology students have access to numerous research journals and online databases. Students get access to specialised publications covering biotechnology, bioinformatics, pharmaceuticals, and environmental science. This helps them with their research work, projects, and assignments. Using these journals, students can learn about the latest techniques, innovations, and experiments happening globally. Such exposure helps them prepare for conferences, workshops, and even competitive exams that require updated knowledge. It also provides students with the opportunity to consult authentic scientific work when working on papers or patents. Overall, having access to these resources enhances their academic and research skills, making them more confident in scientific discussions.

Access to updated journals and research databases is very important for biosciences students, and it is made available for them. This is clear from the fact that in different fields like mycology, insect taxonomy, industrial microbiology, nutraceuticals, and bioremediation, students and researchers are actively publishing their work. Till now, more than 230 + papers have been published, which shows continuous use of such resources. Also, with 2 patents already granted and 3 more filed, students are working on innovative ideas that come only after reading updated scientific content. These journals give exposure to international research methods, modern experiments, and recent case studies. For example, in areas like antimicrobials or animal biotechnology, students can follow new trends directly from global research papers. With such access, biosciences students can stay updated, improve their knowledge, and also think about creating their own research contributions.