Prince Sachan’s Post

During week 10 of the 100xDevs Cohort 2.0, led by Harkirat Singh, we delved into the intricacies of database technologies and their applications. The session covered: 1. A comprehensive overview of popular database systems, including NoSQL, SQL, Graph, and Vector databases. 💾 2. An in-depth comparison of SQL and NoSQL databases, highlighting their distinctive features and use cases. 🔍 3. An exploratory deep dive into PostgreSQL, featuring its cloud counterpart, NeonDB, to understand its robust capabilities. 🚀 4. A practical guide to utilizing 'psql' and the 'pg' library for effective database management. 🛠️ 5. The concept of Connection Strings and their significance in establishing secure database connections. 🔐 6. A clear explanation of database relationships and foreign keys, fundamental concepts for database integrity and relational data modeling. 🔗 7. An examination of SQL Joins, including the various types and their specific uses in querying relational databases. 🤝 The class was designed to equip participants with a solid understanding of database systems, enhancing their ability to develop and manage data-driven applications effectively. 🌟

Level up your Postgres expertise with EDB’s January 2025 free virtual workshops 👇 These five sessions are crafted for technical professionals who want to master PostgreSQL, explore AI-powered Postgres solutions, and optimize database management at scale. Each session is built around real-world use cases and practical insights you can immediately apply to your work. Workshop schedule: 🔸 Designing and Managing Databases in EDB Postgres Master database design, access control, and performance tuning. 🗓️ Jan 8, 12:00 pm IST / 10:00 am ET 🔸 Introducing the EDB Postgres AI Platform Learn how AI-powered Postgres can enhance data management and performance. 🗓️ Jan 9, 12:00 pm IST / 10:00 am ET 🔸 EDB Postgres System Architecture Dive deep into the architecture—storage, memory, transaction processing, and more. 🗓️ Jan 15, 12:00 pm IST / 10:00 am ET 🔸 Postgres Data Estate Management using EDB Postgres AI Learn AI-driven strategies to optimize your Postgres data estate. 🗓️ Jan 22, 12:00 pm IST 🗓️ Jan 30, 10:00 am ET 🔸 Getting to Know the EDB Postgres AI Cloud Service Explore how EDB’s AI-powered cloud service simplifies Postgres deployment and management. 🗓️ Jan 29, 12:00 pm IST / 10:00 am ET Register here 👉 https://bit.ly/3TOO19v #EDBPostgresAI #FreeWorkshop #PostgreSQL #DataEstateManagement #CloudDatabase #DatabaseMigration #DBA #FutureOfAI #JustSolveItWithPostgres

Important paper from the goat: Michael Stonebraker My main takeaways: 1. The relational model and SQL continue to dominate the database landscape, despite repeated attempts to replace them over the past few decades. SQL has absorbed many of the best ideas from alternative approaches. 2. Many non-relational database systems that started out rejecting SQL (e.g. NoSQL databases) have now added SQL-like interfaces and are converging with relational database systems. This trend will continue. 3. Major advancements in database systems have been primarily in relational database implementations, driven by changing hardware characteristics and the move to cloud computing. Key developments include columnar storage, cloud-native architectures, and data lakes/lakehouses. 4. Specialized database systems for specific data models (e.g. document, graph, vector databases) serve niche markets but are unlikely to displace general-purpose relational systems. Relational systems will continue to add capabilities to support these specialized workloads, and will probably replace them. 5. There is a lot of hype around new database technologies, but many end up being repackaged versions of old ideas. We should learn from history and build on proven foundations rather than constantly reinventing database concepts. paper: https://lnkd.in/e-NH5aZQ Also checkout the original 2006 paper: "What Goes Around Comes Around" https://lnkd.in/eaWNkRKn

Understanding Types of Databases Explore the fascinating world of databases with InfosecTrain! From relational databases like MySQL and NoSQL. Our Article simplifies the differences, use cases, and benefits of each. Whether you're a beginner or a seasoned IT pro, gain valuable insights to choose the right database for your projects. Don’t miss this essential guide—unlock your data management potential today! More Info: - Click 👉 https://lnkd.in/gpsZ3jdr for Understanding Database Types

Here to share that I received course completion certificate of 'Introduction to MongoDB' provided by MongoDB. An introductory MongoDB course covers document-oriented storage, where data is stored in flexible JSON-like documents within collections and databases. It includes data modeling, CRUD operations, and indexing for query performance. The course also explores the aggregation framework, replication for high availability, sharding for scaling, and transactions for ACID properties. Security measures like authentication and authorization, along with backup and restore strategies, are discussed. Performance tuning techniques are also taught to optimize database operations. Key Concepts: ✅Data Modeling ✅CRUD Operations ✅Aggregation Framework ✅Sharding & Transactions ✅Backup & Restore ✅Performance Tuning It has introduced me to the Database realm, where the data is stored and managed on multiple factors that provide security and good performance to the data. #MongoDB #Database #Data #Management #NoSQL #CRUD #Framework #Transactions #Backup #Restore #Performance

Elevate your PostgreSQL performance with Vector DB’s advanced features. From advanced query optimization to seamless machine learning integration, Vector DB enhances your database capabilities. Discover how Newt Global empowers your PostgreSQL deployments to deliver faster analytics and greater scalability. https://lnkd.in/drYNvW3H #newtglobal #DMAP #PostgreSQL #VectorDB #database #ML

It is possible to make PostgreSQL horizontally scalable (like NoSQL), by using a combination triggers, views, foreign data wrappers and the concept of consistent hashing with virtual nodes. A simpler approach, without consistent hashing is also possible: 1. Create PostgreSQL instances spread across multiple machines. 2. Data can be partitioned by user/account ID, and all the data associated with them can be group together. For example, if the instance db_vm_i stores user-x, db_vm_j can store user-y and so on. The user-id can be the partition key. 3. Replication can be setup, and to search for a user, a query similar to map-reduce can be used. 4. When data is written, it gets randomly routed to a storage node. Or a more complex setup using views, FDW and consistent hashing can be implemented, and triggers can be use to "wire up" different partitions such that they act in a perfect synchrony. This complex setup, could actually simplify the burden of crafting extremely convoluted queries to perform even the most simple operations on these virtual distributed tables.

I've noticed a lot of buzz lately 😅 so I'm dropping a reference to something we have released and used for a while (since March): Apache Iceberg support for Oracle Autonomous Database! Querying data in OCI and AWS. If you want to know how you can easily query 🔎 #Iceberg data format, check the blog! Andreea Manolescu Semra Selim Andrei Marcov Theodore Kartsonakis Kalju Rüütli Edgars Rungis Robertas Balkys Matthew Kowalik Robert Mikołajczyk Herman Kireccioglu Robert Korosec Slavomir Seno #oracle #adb #iceberg #apacheiceberg #datalakehouse

𝗗𝗮𝘆 𝟭𝟬: 𝗖𝗵𝗮𝗿𝗮𝗰𝘁𝗲𝗿𝗶𝘀𝘁𝗶𝗰𝘀 𝗼𝗳 𝗠𝗼𝗻𝗴𝗼𝗗𝗕 MongoDB, a popular NoSQL database, is known for several key characteristics that distinguish it from traditional relational databases. Here are some of its main characteristics: 𝗗𝗼𝗰𝘂𝗺𝗲𝗻𝘁-𝗢𝗿𝗶𝗲𝗻𝘁𝗲𝗱 𝗦𝘁𝗼𝗿𝗮𝗴𝗲: 𝗗𝗮𝘁𝗮 𝗦𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲: Stores data in JSON-like documents (BSON format), which allows for a flexible and dynamic schema. 𝗦𝗰𝗵𝗲𝗺𝗮 𝗙𝗹𝗲𝘅𝗶𝗯𝗶𝗹𝗶𝘁𝘆: Each document can have a different structure, allowing for easy schema evolution and agility in application development. 𝗦𝗰𝗮𝗹𝗮𝗯𝗶𝗹𝗶𝘁𝘆: 𝗛𝗼𝗿𝗶𝘇𝗼𝗻𝘁𝗮𝗹 𝗦𝗰𝗮𝗹𝗶𝗻𝗴: Supports horizontal scaling through sharding, where data is distributed across multiple servers. 𝗛𝗶𝗴𝗵 𝗔𝘃𝗮𝗶𝗹𝗮𝗯𝗶𝗹𝗶𝘁𝘆: Provides high availability with replica sets, ensuring data redundancy and failover capabilities. 𝗜𝗻𝗱𝗲𝘅𝗶𝗻𝗴: Rich Indexing Capabilities: Supports various types of indexes like single field, compound, geospatial, and full-text indexes to optimize query performance. 𝗥𝗲𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻: Replica Sets: Implements replication via replica sets, which consist of a primary node and multiple secondary nodes, enhancing data durability and read performance. 𝗦𝗵𝗮𝗿𝗱𝗶𝗻𝗴: Partitioning: Supports sharding, enabling data distribution across several machines for horizontal scalability. Automatic Balancing: Automatically balances data across shards to maintain even distribution.

There's a lot of misconceptions about NoSQL databases. (By NoSQL here, I mean document databaess, ordered key value stores, and all points in between). One big one is that they are not all schema-less. Some have internal mechanisms to enforce schema, some don't. Some rely on an application layer to do it. But some relational databases also define their schemas in the application layer as well (one reason people love ORMs!). At the end of the day, you can control what goes in and what goes out of any database. Whether you do or not comes down to dev culture. I'm not some kind of NoSQL evangelist. But nor am I a detractor. And if you want to make guarantees about what goes into such databases, that's entirely within your power.