MongoDB User Group Pune’s Post

🌟 Thanking Our Exceptional Speakers! 🎤 We extend our sincere appreciation to our outstanding speakers for generously sharing their expertise and insights during our meetup - Unlocking power of Data: MongoDB and AWS in action. Your invaluable contributions played a pivotal role in making the event an overwhelming success! #mongodb #mugpune #databases #pune 

🚀 Exciting News Alert! 🚀 I just attended an incredible webinar hosted by #MongoDB and Ade W. on "Intro to Atlas Search"! 🌟 Discover how Atlas Search combines the power of Apache Lucene with the efficiency, scale, and resilience of MongoDB Atlas to seamlessly integrate fast, relevance-based search capabilities into all MongoDB applications. Whether you're dealing with text, numbers, dates, or geoJSON, this webinar showcased a range of search capabilities that will transform your MongoDB experience! A huge thanks to MongoDB for giving me this opportunity to learn and grow! #AtlasSearch #MongoDB #TechInnovation

Thrilled to share that I have successfully completed the MongoDB Associate SI Certification, which covers the fundamentals of MongoDB technology, including the document model, CRUD operations, indexing, and aggregation also its value proposition, and how it addresses customer challenges. #mongodb #nosql #certification #continuouslearning

🚀 New Blog Alert! 🚀 Hey everyone, I’m excited to share my latest blog post on How to Persist Grafana Meta Data in AWS RDS Postgres. If you're looking to optimize your Grafana setup and ensure your data is securely stored and easily accessible, this guide is for you! 🔗 Check it out here: https://lnkd.in/gkYYHYeE Feel free to read, share, and let me know your thoughts! #Grafana #AWS #RDS #Postgres #DataManagement #TechBlog STITCH MES Auriga IT Nishant Gauttam Deepak Jairamani Sarthak Khandelwal Himani Sharma Ronak Singhavi Nisha Saini Pooja Nankani

🚀 Just attended the "Intro to Atlas Search" webinar organized by MongoDB! 🌟 It was an incredible session where we explored the power of Atlas Search, combining Apache Lucene's technology with MongoDB Atlas. The session covered: 🔍 Searching through various data types (text, numbers, dates, geoJSON) ⚙️ Demonstrating diverse search capabilities 📈 Understanding the efficiency, scale, and resilience of MongoDB Atlas A big thanks to the MongoDB team for organizing this insightful webinar. #MongoDB #AtlasSearch #Webinar #DataSearch #TechInnovation

🎉 2 Days Left Until Our Meetup! 🚀 Time is flying by! In just two days, we'll be kicking off an exciting event filled with valuable insights, engaging discussions, and networking opportunities galore. Whether you're a seasoned pro or just starting your journey with AWS and MongoDB databases, there's something for everyone. Dheeraj Choudhary Vishal Alhat ☁️ #awscommuntiy #awsusergroups #awsugpune #databases #pune

HNSW Vector Index: Now Generally Available! #AzureCosmosDB for #MongoDB proudly introduces the general availability of the HNSW Vector Index, a leap forward in AI-driven database capabilities. https://lnkd.in/eWafQcgi

HNSW Vector Index: Now Generally Available! #AzureCosmosDB for #MongoDB proudly introduces the general availability of the HNSW Vector Index, a leap forward in AI-driven database capabilities. https://lnkd.in/ey3Z772q

Why Marry #MongoDB and #Elasticsearch When You Can Have It All with #SingleStore Kai? For anyone trying to bridge MongoDB's robust data handling with Elasticsearch's search prowess, the blog explores several integration methods, from using the MongoDB Connector to custom scripts. While these options work, they come with complexities. But there's a smarter way—SingleStore Kai™, which streamlines data handling with a single solution that's faster, scalable, and simpler to implement. Curious? Dive into the details here. https://lnkd.in/dJKEQVad #BigData #MongoDB #Elasticsearch #DataIntegration

Hare Krishna ! ➡️ In Databricks PySpark , Different ways to sort the data in Ascending or Descending Order 1. df.sort(df.Country.asc()).show() 2. df.sort("Country",ascending=True).show() 3. df.sort(asc("Country")).show() 4. df.sort(col("Country").asc()).show() 5. df.orderBy(col("Country").asc()).show() #Databricks #Azuredatafactory #Spark #Azuredatabricks #Apachespark #pyspark #Cloud #dataengineer #dataanalysis #dataanalyst