Real-Time Unified Data Layers: A New Era for Scalable Analytics, Search, and AI v 1.1Table of Contents Introduction 1. The Interconnection of Analytics, Search, and AI 2. What is a Real-Time Unified Unified Data Layer? 3. Why Do You Need a Real-Time Unified Data Layer? 4. 5.CrateDB: A Modern Real-Time Unified Data Layer1. Introduction Data teams are facing more challenges than ever. As applications data engineering and architecture teams must design systems that not only scale but also deliver real-time access and insights. However, the complexity isn’t just technical—business expectations have grown

using a wave digital voltage source, resistor, and capacitor, all connected with a series adaptor. Real-Time Circuit Simulation with Wave Digital Filters in C++ Author: Jatin Chowdhury Affiliation: Chowdhury of their sound-processing algorithms. Given that audio effects are typically required to run in “real-time”, traditional circuit modelling softwares (e.g. LTSpice) are typically not suitable for this purpose Filters, allowing the user to quickly and easily construct circuit simulations that are suitable for real-time applications. Wave Digital Filters Wave Variables Wave Digital Filters (WDFs) use “wave variables”

Inc.iZotope real-time audio plug-ins | music, film, television, and radio iZotope Inc.iZotope real-time audio plug-ins | music, film, television, and radio iZotope Inc.iZotope real-time audio plug-ins plug-ins | music, film, television, and radio iZotope Inc.iZotope real-time audio plug-ins | music, film, television, and radio iZotope Inc.Glass Properties Making a legacy run-time system compile-time safe - Hosts can call us from any thread - Each host may do this this differently Challenges for real-time audio plug-ins Confidential property of iZotope Inc.Canvas (ca. 2002)JUCE (ca. 2004) Canvas

??? Vasiliki Kalavri | Boston University 2020 CS 591 K1: Data Stream Processing and Analytics Vasiliki (Vasia) Kalavri
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Vasiliki Kalavri | Boston University 2020 CS 591 K1: Data Stream Processing and Analytics Vasiliki (Vasia) Kalavri
 vkalavri@bu.edu Spring 2020 2/25: State Management Vasiliki Kalavri | Boston

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 vkalavri@bu.edu Spring 2020 4/14: Stream processing optimizations ??? Vasiliki operator shares a lock with an upstream operator. • Satisfy deadlines: for applications with real-time constraints or QoS latency constraints. Batching Process multiple data elements in a single batch

Vasiliki Kalavri | Boston University 2020 CS 591 K1: Data Stream Processing and Analytics Vasiliki (Vasia) Kalavri
 vkalavri@bu.edu Spring 2020 2/11: Windows and Triggers Vasiliki Kalavri | Boston input • e.g. joins, holistic aggregates • Compute on most recent events only • when providing real-time traffic information, you probably don't care about an accident that happened 2 hours ago • Recent

Vasiliki Kalavri | Boston University 2020 CS 591 K1: Data Stream Processing and Analytics Vasiliki (Vasia) Kalavri
 vkalavri@bu.edu Spring 2020 1/21: Introduction Vasiliki Kalavri | Boston University 20% 7 Vasiliki Kalavri | Boston University 2020 Grading Scheme (2) Final Project (50%): • A real-time monitoring and anomaly detection framework • To be implemented individually Deliverables • Kalavri | Boston University 2020 Final Project You will use Apache Flink and Kafka to build a real-time monitoring and anomaly detection framework for datacenters. Your framework will: • Detect “suspicious”

University 2020 Vasiliki (Vasia) Kalavri
 vkalavri@bu.edu CS 591 K1: Data Stream Processing and Analytics Spring 2020 2/06: Notions of time and progress Vasiliki Kalavri | Boston University 2020 Mobile

Vasiliki Kalavri | Boston University 2020 CS 591 K1: Data Stream Processing and Analytics Vasiliki (Vasia) Kalavri
 vkalavri@bu.edu Spring 2020 1/23: Stream Processing Fundamentals Vasiliki Kalavri than being available in full before its processing begins. • Data streams are high-volume, real-time data that might be unbounded • we cannot store the entire stream in an accessible way • we have pre-aggregated, pre-processed streams and historical data Data Management Approaches 4 storage analytics static data streaming data Vasiliki Kalavri | Boston University 2020 DBMS vs. DSMS DBMS DSMS