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14 Top Data Pipeline Key Terms Explained

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 Here are some key terms commonly used in data pipelines 1. Data Sources Definition: Points where data originates (e.g., databases, APIs, files, IoT devices). Examples: Relational databases (PostgreSQL, MySQL), APIs, cloud storage (S3), streaming data (Kafka), and on-premise systems. 2. Data Ingestion Definition: The process of importing or collecting raw data from various sources into a system for processing or storage. Methods: Batch ingestion, real-time/streaming ingestion. 3. Data Transformation Definition: Modifying, cleaning, or enriching data to make it usable for analysis or storage. Examples: Data cleaning (removing duplicates, fixing missing values). Data enrichment (joining with other data sources). ETL (Extract, Transform, Load). ELT (Extract, Load, Transform). 4. Data Storage Definition: Locations where data is stored after ingestion and transformation. Types: Data Lakes: Store raw, unstructured, or semi-structured data (e.g., S3, Azure Data Lake). Data Warehous...
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RDBMS Vs NOSQL awesome differences to read now

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NoSQL and RDBMS or SQL are different from each other. You may ask what is the difference. Below explained in a way that you can understand quickly.

rdbms vs no sql

💡Traditional Database

  • A schema is required. All traditional data warehouses using RDBMS to store datamarts.
  • Databases understand SQL language. It has a specific format and rules to interact with traditional databases.
  • Less scalable. It has certain limitations. 
  • Expensive to make the databases as scalable
  • Data should be in a certain format.
  • Data stored in row format.

NoSQL database

The growing internet usage and involving a number of devices caused to invent databases that have the capability to store any kind of data.

NoSQL Special Features
  • The schema is not required. Ability to handle multiple data types. This is the power of NoSQL.
  • NoSQL is much suitable for analytical databases. Since those should be flexible, scalable, and able to store any formatted data.
  • The increased usage of web applications, the availability of broadband for the common man, caused the generating of a variety of data. So NoSQL is absolutely needed for the new generation businesses.
  • Data stored in column format. In the form of key-value pairs.
  • Python, Ruby, PHP, and Java are top languages you need to interact with NoSQL databases.

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