2.1. Theory About

  • Rodzaje baz danych (RDBMS, RDSMS, Non-rel)

  • Relacyjne bazy danych (SQLite3, PostgreSQL, Oracle, MSSQL, MySQL)

  • Nierelacyjne bazy danych (Timeseries, Graph, Document)

  • Sorted Query Language (SQL)

  • SQL vs NoSQL vs NewSQL

  • ORM

  • Normalizacja danych

  • Postaci normalne

  • Dobre praktyki

2.1.1. RDBMS


Relational Database Management System https://en.wikipedia.org/wiki/Relational_database#RDBMS


Relational Data Stream Management System https://en.wikipedia.org/wiki/Relational_data_stream_management_system

2.1.2. Big Data


Big data is a field that treats ways to analyze, systematically extract information from, or otherwise deal with data sets that are too large or complex to be dealt with by traditional data-processing application software. Data with many fields (columns) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate. Big data analysis challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating, information privacy, and data source. Big data was originally associated with three key concepts: volume, variety, and velocity. The analysis of big data presents challenges in sampling, and thus previously allowing for only observations and sampling. Therefore, big data often includes data with sizes that exceed the capacity of traditional software to process within an acceptable time and value. [1]

2.1.3. References