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What kind of database does WhatsApp use for the back end?

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Title: Unveiling WhatsApp's Data Foundation: Database Technology Powering AI Automation Introduction: As an experienced tutor registered on UrbanPro.com, understanding the database technology behind WhatsApp's backend is crucial for learners entering the AI automation landscape. Let's explore the...
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Title: Unveiling WhatsApp's Data Foundation: Database Technology Powering AI Automation

Introduction: As an experienced tutor registered on UrbanPro.com, understanding the database technology behind WhatsApp's backend is crucial for learners entering the AI automation landscape. Let's explore the intricacies of WhatsApp's data foundation through a structured and informative format.

1. Overview of WhatsApp's Database Technology:

1.1. Volume and Complexity:

  • WhatsApp: Manages a massive volume of user data, messages, and multimedia content.

1.2. Database Architecture:

  • Key Components: WhatsApp employs a mix of relational and NoSQL databases for optimal performance.

2. Relational Databases in WhatsApp's Backend:

2.1. MySQL:

  • Usage: WhatsApp started with MySQL for user data storage.
  • AI Automation Application: Facilitates structured data storage crucial for AI models relying on well-defined user profiles.

2.2. PostgreSQL:

  • Usage: Certain features might utilize PostgreSQL for relational data.
  • AI Automation Application: Supports specific AI-driven applications requiring the features of PostgreSQL.

3. NoSQL Databases in WhatsApp's Backend:

3.1. Erlang-based Mnesia:

  • Usage: WhatsApp's original message store was implemented using Mnesia.
  • AI Automation Application: Suits real-time message storage and retrieval in AI-driven applications.

3.2. Cassandra:

  • Usage: WhatsApp has integrated Cassandra for scalability in handling message data.
  • AI Automation Application: Ideal for managing large-scale datasets in AI model training and real-time message analytics.

4. AI Automation Application of WhatsApp's Database Technology:

4.1. Real-time Messaging:

  • Structured Data: Relational databases store user profiles.
  • Unstructured Data: NoSQL databases handle real-time messaging data, crucial for AI-driven chat applications.

4.2. Multimedia Content Handling:

  • Efficient Storage: NoSQL databases like Cassandra handle multimedia content efficiently, supporting AI algorithms processing multimedia data.

5. UrbanPro.com: Your Gateway to Database Expertise:

5.1. Expert Coaching on UrbanPro:

  • UrbanPro.com connects learners with experienced tutors specializing in AI automation coaching, offering insights into database technology, including examples from platforms like WhatsApp.

5.2. Practical Application:

  • Tutors on UrbanPro provide hands-on coaching, allowing learners to understand and apply database concepts based on real-world examples like WhatsApp's backend.

6. Conclusion: Understanding WhatsApp's database technology is pivotal for AI automation enthusiasts. UrbanPro.com stands as the best online coaching platform, connecting learners with experienced tutors who provide personalized guidance and hands-on coaching in database concepts, ensuring learners are well-equipped for success in the dynamic field of AI automation.

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What are the job operations related to DBMS after mca ?
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