NoSQL

1. Flexible Data Models: Support for diverse data models like key-value, document-oriented, columnar, or graph-based structures.

2. Horizontal Scalability: Ability to scale horizontally across multiple nodes for handling large volumes of data and high transaction rates.

3. Schema-less or Dynamic Schema: Flexibility in data modeling with no rigid schema enforcement, allowing for easier schema evolution.

4. High Performance: Optimized for low-latency data access and high throughput, suitable for real-time and high-volume data applications.

Before learning NoSQL, it's beneficial to have skills in:

1. Database Fundamentals: Understanding of basic database concepts such as data modeling, querying, and data manipulation.

2. Data Structures and Algorithms: Familiarity with data structures and algorithms, as NoSQL databases often require understanding of different data models.

3. Programming: Proficiency in at least one programming language like Python, JavaScript, or Java for interacting with NoSQL databases through APIs.

4. Database Query Languages: Knowledge of query languages like SQL (Structured Query Language) and NoSQL query languages such as MongoDB's query language or Cassandra's CQL (Cassandra Query Language).

By learning NoSQL, you gain skills in:

1. Data Modeling: Ability to design and implement data models suited for various NoSQL databases, considering factors like scalability and performance.

2. Database Administration: Proficiency in managing NoSQL databases, including installation, configuration, and monitoring.

3. Querying and Data Manipulation: Skills in querying and manipulating data using NoSQL query languages or APIs.

4. Scalability and Performance Optimization: Understanding of techniques for optimizing performance and scalability in distributed NoSQL environments.