Sad Reality of The Justice System

Just for laugh

:soccer: 𝙵𝚘𝚘𝚝𝚋𝚊𝚕𝚕 𝚅𝚜 𝙱𝚕𝚊𝚌𝚔 :frowning:





IᑎᔕTᗩGᖇᗩᗰ ( instagram.com :heart:

𝙱𝚕𝚊𝚌𝚔 𝙻𝚘𝚟𝚎𝚛𝚜 ( instagram.com :white_check_mark:

#Laravel devs, whenever you're tempted to call abort(403), remember that you never have to do that. :nail_care:

:heart:Hit n Run:heart_eyes:#God (DC@IMPULSE:black_heart:) #justcallmeklaus #nasieku #theealfahouse #shotsbygkydd

:round_pushpin: Babatunde Palace

My mother, my wife, my sister, my daughter

To the ones who gave birth to humanity…Everything began with you…they cannot ignore your worth and power

You truly are the real queen :crown::crown::crown::crown:

#Sundiata #SpiritOfNewAfrica

NoSQL vs SQL

NoSQL databases provide flexible data models ideal for diverse data structures and scalability.

1. Key-Value: Simple, uses key-value pairs (e.g., Redis).
2. Document: Stores data in JSON/BSON documents (e.g., MongoDB).
3. Graph: Manages complex relationships with nodes and edges (e.g., Neo4j).
4. Column Store: Optimized for analytics, organizes data by columns (e.g., Cassandra).

SQL databases, like RDBMS and OLAP, pro... see more NoSQL vs SQL

NoSQL databases provide flexible data models ideal for diverse data structures and scalability.

1. Key-Value: Simple, uses key-value pairs (e.g., Redis).
2. Document: Stores data in JSON/BSON documents (e.g., MongoDB).
3. Graph: Manages complex relationships with nodes and edges (e.g., Neo4j).
4. Column Store: Optimized for analytics, organizes data by columns (e.g., Cassandra).

SQL databases, like RDBMS and OLAP, provide structured, relational storage for traditional and analytical needs

1. RDBMS: Traditional relational databases with tables (e.g., PostgreSQL & MySQL).
2. OLAP: Designed for complex analysis and multidimensional data (e.g., SQL Server Analysis Services).

Cristiano Ronaldo’s incredible goal is even better from this angle. 🤯

🤯 You Won't Believe How Much an iPhone Really Costs
@haksncraks :white_check_mark: