Neo4j’s Post

PropelZ is the new fast, #nocode utility for extracting #mainframe #data. Watch the demo here: https://lnkd.in/gXQkhAQW. Install today, propel your data today. https://lnkd.in/gRFqmdqN #dataaccess #etl #elt VirtualZ Computing #datalake #datawarehouse

🛠️ Explore the different Change Feed modes in #AzureCosmosDB! Learn how to efficiently process data changes in your applications. Discover more here: https://lnkd.in/eiRubb97 🚀

Is your team using the right compute engine for the right job? If not, it could be costing you thousands or hundreds of thousands of dollars. - 30% to 40% of a company's queries are for ad hoc and development work. - 91% of these ad hoc queries are less than 10GBs. Does it make sense to use data platform compute for queries this small or even at all? We don't think so. This is why we built Coginiti Hybrid Query. Every Coginiti product embeds a highly performant analytics query engine, eliminating most of the cost for ad-hoc analysis and development. Learn more and sign up for our private preview: https://lnkd.in/eF3e3FXm

🛠️ Explore the different Change Feed modes in #AzureCosmosDB! Learn how to efficiently process data changes in your applications. Discover more here: https://lnkd.in/ezSm-ShT 🚀

🗣️ ICYMI - Web3Bench is here! Get all the details on the new hybrid transaction / analytical processing (HTAP) benchmark for Web3 workloads. Learn why we need a HTAP benchmark, how to get started, and see results from HTAP benchmark testing. 🧪 #HTAP #Web3 #TiDB https://lnkd.in/ghph5U5s

Say goodbye to slow queries and hello to Yellowbrick, the modern data warehouse built for speed and elasticity in the age of Kubernetes. Here's how Yellowbrick breaks the mold: ✅ Runs on Kubernetes: Leverage the power and flexibility of Kubernetes for effortless scaling and cloud portability. No more being locked into proprietary hardware! ✅ Massively Parallel Processing (MPP): Unleash the power of parallel processing for lightning-fast queries, even on petabyte-scale data. ⚡️ ✅ Guaranteed sub-second response times: Get actionable insights instantly, no matter how complex your queries or how many users are accessing the data. ⏱️ ✅ Simple and predictable pricing: Avoid the cost surprises of traditional data warehouses. Yellowbrick's transparent pricing lets you budget effectively. ✅ Open standards: No vendor lock-in! Yellowbrick is built on open standards for ultimate flexibility and future-proofing. Ready to ditch the data warehouse drag? Head over to https://okt.to/TZP3F8 and see how Yellowbrick can take your analytics to the next level.

Exciting news! SingleStore 8.5 is here with a host of enhancements: #VectorSearch: Improved processing and performance with features like indexed approximate-nearest-neighbor search and a new VECTOR data type. #SQLImprovements: INSERT...ON DUPLICATE KEY now supports DELETE, increased name length limits, and streamlined maintenance of aggregates. #Programmability: Support for extensions, new table%rowtype and tablecolumn%type notation, easing code creation and porting from Oracle. #Monitoring: Query history support for detailed tracking, simplifying application performance monitoring. #Performance Boost: ORDER BY/LIMIT queries perform better, over a dozen query optimization improvements, and enhancements for JSON and Kai. #Miscellaneous: Shallow table copy for near-instant copying of large tables with minimal storage overhead. ... and a lot more Save the date: Jan. 24th 2024 launch event! Join us to explore these incredible features and our latest cloud platform enhancements. Check the forum post and 8.5 release notes for more details! #SingleStore #ReleaseAnnouncement #TechNews https://lnkd.in/dJHvY2ir

🚀Confluent acquires Warpstream! 💿Using Object Storage like S3 for data persistence is now becoming mainstream. The scalability and decoupling benefits that object storage provide outweigh its pitfalls (latency, not a real Filesystem), which is why more systems are looking into S3 as data storage layer. 📜Expect a blog on how Object storage is becoming mainstream for persisting data instead of file systems! https://lnkd.in/diYTbY_x #dataengineering #softwarearchitecture

It's super important to set up distributed tracing, metric and observability! Just turn it on before you need it. Connecting that request all the way from the frontend, all the way through the API gateway and one or more backend services. In #dotnet it's the matter of switching to a new library, with some setup code changes in your program.cs minimal effort great value! #mvpbuzz

A few things which should immediately strike your mind: 1. Static Websites on AWS: S3 2. Protocol for one to one video call(Zoom/Skype): WebRTC(Runs over UDP) 3. Protocol for Live Streams or Webinars(Zoom/YouTube Live): RTMP(Runs over TCP) 4. Protocol for Peer to Peer Chat App(Whatsapp): WebSockets 5. Algorithm for Collaborative Editing(Google Docs): Operational Transformation 6. Protocol for peer to peer Collaborative Editing(Google Docs): WebSockets 7. CDNs: Consistent Hashing 8. Fanning: Caching 9. In Memory: Caching 10. Database Scaling: CAP theorem 11. Distributed Systems: Latency, Point of Failures, Circuit Breakers, CAP Theorem 12. Database for Proximity Apps(Uber, Yelp): Geospatial Databases 13. Likes/Views on YouTube: Eventual Consistency 14. Transactions in Payment Systems: Strong Consistency 15. Few secs Lags in a live Cricket Match: Acceptable 16. Few Secs Lag on a Video Call: Nightmare 17. Instagram Pics Storage: Object Storage 18. Databases for storing connections(Friends list on Facebook): Graph DB 19. Cloud: More Latency than Data Center 20. NoSQL: Probably you will never need Cheers!!!!!.