9 Questions
What are the four characteristics of data management systems that are particularly important for large-scale data management tasks?
Scalability, Flexibility, Availability, Cost
What is the definition of Velocity in the context of Big Data?
The speed at which data is generated, processed, and made available
Relational databases are less flexible in terms of schema compared to NoSQL databases.
True
______ databases offer an alternative to traditional relational databases, particularly for applications that require scalability, flexibility, and high performance across distributed systems.
NoSQL
What are the four main types of NoSQL databases listed in the content?
Key-Value Databases, Document Databases, Column-Family Stores, Graph Databases
What is the name of the database represented by MS Azure DocumentDB?
DocumentDB
What advantage of NoSQL databases is related to the ability to handle large volumes of diverse data?
Flexibility
What is one of the challenges associated with NoSQL databases that is related to the ability to maintain uniform data?
Data Consistency
Which of the following are advantages of NoSQL databases? (Select all that apply)
Scalability
Study Notes
Recap of Previous Week
- Course structure: Quizzes (5%), Homework (10%), Project (25%), Midterm Exam (30%), Final Exam (30%)
- Assessment details: Quizzes, Homework, Project, Midterm Exam, Final Exam
- Books and Resources: NoSQL for Mere Mortals by Dan Sullivan, Seven Databases in Seven Weeks by Luc Perkins, Eric Redmond, and Jim R. Wilson
The Importance of Data
- Big Data: high volume, high velocity, and/or high variety information assets that require new forms of processing to enable enhanced decision making, insight discovery, and process optimization
- Sources of Big Data: social media and networks, IoT devices, web logs and browsing data, transactional data
- Characteristics of Big Data: Volume, Velocity, Variety
The Three Vs of Big Data
- Volume: the amount of data, requiring distributed storage solutions and horizontal scalability
- Velocity: the speed at which data is generated, processed, and made available, requiring real-time or near-real-time processing and analysis
- Variety: the different types of data, including structured, semi-structured, and unstructured data, requiring flexible schema or even schema-less databases
Types of Data
- Structured Data: adheres to a strict schema or format, often found in relational databases, easy to query and searchable
- Semi-Structured Data: has some organizational properties, can be transformed into structured data, offers flexibility in data capture
- Unstructured Data: doesn't have a specific form or model, represents a vast majority of data in the digital world, crucial for sentiment analysis, recommendation systems, etc.
Motivation for NoSQL Databases
- Scalability: efficiently meet the needs of varying workloads
- Flexibility: flexibility in the range of problems that can be addressed using relational data models
- Availability: NoSQL databases are designed to take advantage of multiple, low-cost servers
- Cost: the cost of database licenses, open-source software avoids these issues
What is a Non-Relational (NoSQL) Database
- represents a broad category of database management systems that differ from traditional relational databases
- designed to overcome the limitations of relational databases, particularly for applications that require scalability, flexibility, and high performance across distributed systems
Relational vs. Non-Relational Databases
- Data Model: structured vs. flexible schema
- Scalability: vertical scaling vs. horizontal scaling
- Consistency: ACID vs. BASE
- Use Cases: traditional relational databases vs. applications requiring specialized mechanisms for data storage and retrieval
ACID vs. BASE
- ACID: Atomicity, Consistency, Isolation, Durability, ensuring data integrity
- BASE: Basically Available, Soft state, Eventual Consistency, a compromise between consistency and availability
Relational vs. Non-Relational vs. Data Lakes
- Data Model: structured, flexible, or no predefined schema
- Scalability: vertical, horizontal, or distributed systems
- Transaction Support: ACID transactions, eventual consistency, or not focused on transactions
- Use Cases: traditional relational databases, applications requiring flexibility and scalability, big data analytics and data lakes
Explore the motivations and importance of NoSQL databases, including scalability, flexibility, and cost. Learn about the differences between relational and non-relational databases, and data lakes.
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