Bill Potter

Big news for teams building real time systems on Oracle Cloud. DeltaStream is now partnering with the Oracle Cloud team to make streaming analytics on OCI Streaming with Apache Kafka simple and operationally efficient. If you are building event driven systems on Oracle Cloud and want faster time to value from your streaming data, this partnership is worth a look. Read the full partner blog here: https://lnkd.in/gcv3Kyfg Thanks to the DeltaStream team (Hojjat Jafarpour, Rachel Pedreschi, Krishna Raman) and our partners at Oracle (Jason Wilcox, Abhishek Bhaumik, Chris Sullivan, Suresh Patibandla) for helping to kick off this collaboration. #PartnerEcosystem #OracleCloud #OCI #Kafka #RealTimeData #StreamingAnalytics #AIInfrastructure #DeltaStream #DataEngineering #Flink

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One for my DBA friends! A very good talk from Andy Pavlo, looking at how LLMs can _actually_ be used to help improve performance. It's measured and reasonable, with plenty of caveats and real-world considerations along the way from someone who _really_ gets RDBMS. https://lnkd.in/e4JDuKS5

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Great news for Spanner and BigQuery users. Datastream now provides a seamless, serverless bridge from Spanner’s transactional power to the high-performance analytical capabilities of BigQuery and BigLake. Get the most scalable and available database that runs Google with BigQuery and BigLake’s serverless AI-Native Lakehouse!

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People often ask me about the differences in architecture between Amazon Dynamo (the 2007 SOSP paper), DynamoDB (the AWS serverless NoSQL database), and Aurora DSQL (the AWS serverless SQL databases). I captured the key points on durability, high availability, programming model, and trade-offs in my blog: https://lnkd.in/gkMG_tVD TL;DR: Despite the shared name, Dynamo and DynamoDB have little in common architecturally, and make very different trade-off decisions.

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Vitaly sat down with Vinay! They walk through a real-world migration challenge involving Oracle Fusion and Integration Cloud. Manual processes, hidden code and high risk until a custom-built utility and GitLab automation changed everything. This one’s about visibility, governance and solving problems that don’t have off-the-shelf answers. Deepak Agnani Mithun P J Nico Stirling Vitaly Efimov Mayank Kumar Jyotsna Narang Vinay Vaitla Vikalp Sharma Kenil Doshi   #BehindTheCode #BuiltByStrata #StrataStories #DevLife #TechLeadership #SoftwareEngineering #Oracle  

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Can you share a compelling scenario where using an ARRAY column type in #Lakehouse and #Delta makes sense, rather than modeling it as a separate table? Traditionally, arrays are seen as an anti-pattern in relational design, so I’m curious to learn about cases where this approach is truly justified

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There's nothing more exciting than seeing world-class engineers innovate on behalf of customers. Here are three ways Snowflake just got smarter. ✨ Seamless Performance: Powered by Snowflake Optima Optima is our new intelligent optimization engine that automatically accelerates customer workloads. Automatic indexing and query optimizations happen behind the scenes with no knobs or extra effort. As a result, customers are seeing up to 15x faster queries on Gen-2 warehouses with zero additional compute or storage costs. Go here to learn more: https://lnkd.in/gxPBzhQZ 🧠 Empowering SQL Developers Details matter. We're making SQL more expressive, flexible and resilient. MERGE ALL BY NAME simplifies column mapping; updates and inserts happen automatically when names match. CONTINUE handlers let you handle exceptions without breaking flow. And Snowflake Scripting UDFs (now GA) bring full procedural logic directly into SQL. Go here to learn more: https://lnkd.in/gSvnnVew 🚀 Expanded Migration Support: Powered by SnowConvert AI Migrating from legacy systems just got easier. SnowConvert AI now supports more sources than ever including Teradata, Databricks, Oracle, SQL Server, Redshift, Azure Synapse, Google BigQuery, Greenplum, Postgres, Vertica, Hive, IBM DB2 and more. It automatically converts code, procedures and logic into Snowflake-native SQL, helping customers modernize faster and with confidence. Go here to learn more: https://lnkd.in/gX3TqdBT We're focused on making Snowflake faster, smarter and simpler every single day. No tuning. No hacks. Just better engineering under the hood, so builders can focus on building. #Snowflake #AIDataCloud #Optima #Performance #SQL #Migrations

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Keeping cloud architecture diagrams updated across a fast moving environment can feel like an endless game of catch up. With Lucid’s Cloud Accelerator, teams can create reusable assets for frequently used elements like VPCs, databases, and subnets. Update once and watch changes cascade across every diagram, saving time, reducing manual effort, and keeping documentation consistent as your cloud environment evolves. See how you can bring clarity to your cloud journey: https://lnkd.in/gWyKa5tH

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Data zones matter! Learn why we're evolving our #DataLake from a no-zone to multi-zone architecture. Distinguished Engineer Vaidyanathan Kasi shares how distinct zones (raw, standardized, consumption) enable clear data lineage and improved data quality. https://bit.ly/4oxhoen

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