Sharing data between standard Snowflake and China-based accounts can be tricky due to regulatory and architectural barriers. Vinodh Kumar Govindarajan and Sandeep M on the phData team have solutions. Their latest blog outlines practical, real-world strategies for enabling secure, bidirectional data sharing across borders by orchestrating external tables, cloud storage, and smart AWS automation. Ready to move data with confidence? Read the full blog today! 👇 https://lnkd.in/gg2JnkMN
How to share data between Snowflake and China-based accounts securely
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Snowflake is set to be deployed within Amazon Web Services (AWS)’ (Asia Pacific) New Zealand region within the first half of 2026. https://lnkd.in/gDwbd67u The instance will provide Snowflake’s New Zealand customers with an avenue to keep data secure on shore while also tapping into the vendor’s AI Data Cloud. Snowflake New Zealand country manager Tony Shaw said the announcement is a key milestone for the company, as it will allow its customers in the country “to innovate faster and more securely than ever before”.
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This is big! 🚀 Our team(Google Cloud Dataplex Lineage) has rolled out Column Level Lineage for BigQuery. That's an exclusive feature - no other governance/lineage solution provides these level of granularity for the BigQuery! More granular tracking, better governance, and a clearer picture of your data lineage than ever before. And you don't need to pay extra for this - the pricing is the same as for Table Level Lineage! Well done, team! #GoogleCloud #BigQuery #DataGovernance #DataLineage #Dataplex
Thrilled to announce a significant milestone for the Google Cloud Dataplex Lineage team! We've launched Column Level Lineage for BigQuery, providing deeper insights into data provenance. This will enable more granular tracking and better governance for data in BigQuery. Check out the attached GIF to see it in action! Learn more in the official release notes: https://lnkd.in/dRMdDmcT #GoogleCloud #BigQuery #DataLineage #DataGovernance #Dataplex
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Every fails, all the time ... and today probably a bit more than usual 💀 With the recent outage on AWS, it's perfect moment to remember that cloud and distributed systems will eventually fail. Something can always go wrong. Accept this fact and design your systems accordingly, think about all the possible edge cases. What if ... 👉 an API call doesn’t return 200? 👉 you can’t scale your (serverless) infrastructure? 👉 your cloud storage suddenly rejects writes? 👉 your database becomes unreachable? 👉 one of your 8-hour ELT jobs is aborted midway? ... We should compose data pipeline with a subtil mix of state management, immutability, assets managements, reproducibility, idempotency, resilience ... #aws #data #datapipeline
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#MariaDB Cloud simplifies building #AI applications. 🧑💻 Built on the power of MariaDB Server, MariaDB Cloud delivers mission-critical resilience, integrated AI, and multicloud freedom right out of the box. 📦 By integrating high-performance vector search and developer tooling right into the #database, this unified approach eliminates the complexity and cost that fragmented #data stacks have. 💪Ready to build your next application? Get started: http://bit.ly/4mCUUXH
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Single cloud is simple. Multi cloud is freedom if you design for it. I broke down how to build portable, cost-aware pipelines with AWS Glue + Apache Iceberg + lakeFS, so you get flexibility without surprise egress bills or weak metadata. I wrote a practical playbook: AWS Glue for compute, Iceberg for open tables, lakeFS for versioning so your data stays portable and your costs predictable. #DataEngineering #MultiCloud #AWSGlue #ApacheIceberg #lakeFS #MLOps #Cloud #DataPlatforms lakeFS, Apache Iceberg Amazon Web Services (AWS)
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In modern cloud architectures, agility and scalability are everything and that’s exactly what you get when you combine AWS Lambda with Amazon DynamoDB. With this serverless duo, you can build powerful applications that automatically scale, cost only when used, and require zero infrastructure management. Here’s why this combo stands out: ✅ Lambda handles your business logic — event-driven, auto-scaling, and pay-per-execution. ✅ DynamoDB stores your data — fully managed, highly available, and lightning-fast. ✅ Together, they enable event-driven architectures that react instantly to changes — no servers, no patching, no downtime. Whether it’s logging API activity, processing real-time data streams, or powering microservices, Lambda + DynamoDB helps developers move faster and smarter. 💡 Think serverless. Think scalable. Think AWS. #AWS #Serverless #DynamoDB #Lambda #CloudComputing #TechInnovation #Developers #CloudArchitecture
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Origin-to-edge observability for AWS CloudFront, AWS WAF, and AWS Elemental. For companies generating terabytes or even petabytes of log data every day, Hydrolix delivers unmatched speed, scale, and savings. Running natively on Amazon Web Services (AWS), Hydrolix transforms origin and edge services data into critical insights, with hot data retention for 15+ months at up to 75% lower cost than legacy solutions. Hydrolix is redefining real-time analytics for the data-intensive era.
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I published a new article in which I describe a reference architecture for an AWS hosted data platform built entirely from open‑source components, as opposed to managed services. Why open-source? Sure, using managed services can make development faster and will usually simplify operations and security policy compliance. But besides the obvious trade-offs that we often accept (slightly heavier bill, vendor lock-in etc.) there's another aspect which is often not considered: digital sovereignty. Building a cloud-native platform entirely with open-source tools and operating it in EU regions is in-line with the EuroStack initiative, the EU Commission's recent initiative that encourages European businesses to build strategic autonomy across all layers of the stack – from chips and AI frameworks to cloud platforms. Adapting this architecture to Azure or Google Cloud setups will also be fairly straightforward. And if you want to be fully EuroStack-aligned, the next step will be to host the platform on a EU-based OpenStack provider. 🌐 Read more on the our blog: https://lnkd.in/d-B_aCuh
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2nd Episode of Cloud Series: Object Storage "Beyond Cheap Storage: Where Your Data Lives Defines Its Potential." AWS S3: The industry standard. Unmatched ecosystem, durability, and feature set (like S3 Glacier). The default choice for a vast range of applications. Azure Blob Storage: Deeply integrated with Azure services like Data Lake, Synapse, and Power BI. Ideal for analytics and AI on structured/unstructured data. GCP Cloud Storage: Renowned for its performance and consistent pricing (no egress fees to Google's CDN). A powerhouse for data analytics, ML, and serving large assets. OCI Object Storage: Known for its strong consistency model, simple pricing, and high performance, especially when paired with Oracle databases and applications.
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👀 Step inside an AWS data center! Discover our custom-designed power systems & innovative infrastructure in this latest video, "Building Resilient Cloud Services (Part 3)."🍿
Part 3: Building Resilient Cloud Services
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