12^th Workshop on Scalable Cloud Data Management

Workshop

We solicit research on novel database designs and their distribution and storage mechanisms (NoSQL, NewSQL, Database-as-a-Service, real-time databases) as well as scalable data and data-processing services. The application side of cloud databases is equally important, as it might impose new programming models, APIs and web-enabled interfaces. The workshop will bring together cloud computing, data architectures and data-related services from the perspective of scalability and hopes for your contribution to this exciting new field.

This year's workshop is a special edition with a primary emphasis on Web engineering or globally distributed applications. In addition to the usual topics, we encourage submissions that cover website performance tracking, A/B testing, and optimization. Our main interest is in research that investigates how cloud databases can be utilized to meet the requirements of contemporary web applications and services.

Read Call For Papers »

Important Dates

Oct 01 Nov 01, 2023: Due date for full workshop paper submission
Nov 10, 2023: Notification of paper acceptance to authors
Nov 20, 2023: Camera-ready of accepted papers
Dec 15-18 (TBD), 2023: SCDM Workshop

Topics

The workshop covers several modern topics related to cloud computing, NoSQL, scalability, services and databases:

• Database-as-a-Service, Backend-as-a-Service, Multi-Tenancy
• Website Performance Tracking & A/B Testing
• Web Infrastructure Optimization
• Machine Leaning Methods for Data Management
• Elasticity and Scalability for Cloud Data Management Systems
• New Protocols, Service Interfaces, and Data Models for Cloud Databases
• Continuous Query Processing, Streaming Analytics, and Real-Time Databases
• Polyglot Persistence, NoSQL, Schemaless Data Modeling, Integration
• Database Architectures for Mobile and Web Clients
• Content Delivery Networks, Caching, Load-Balancing, Web-Scale Workloads
• Virtualization for Cloud Databases, Storage Structures and Indexing
• Frameworks and Systems for Parallel and Distributed Computing
• Scalable Machine Learning and Data Science
• Resource and Workload Management in Cloud Databases
• Tunable and Eventual Consistency, Latency
• High Availability, Reliability, Failover
• Transactional Models for Scalable Databases
• Consistency, Replication, and Partitioning
• Distributed Schema Management and Evolution