Managing Kafka shouldn’t feel like an endless battle. Yet, for many organizations, it does: 🔹 Setting up clusters, brokers, and configurations 🔹 Tuning for performance and scaling 🔹 Managing downtime, maintenance, & troubleshooting

Connecting @Streamkap to @OleanderHQ has never been easier. Stream your data directly into oleander's fully managed Iceberg REST catalog, then query it with intelligent data compute routing. No clusters. No infrastructure to manage. See it live 👉 oleander.dev/bluehouse?tab=d…

Cons - In addition to the considerations with SMTs above, Flink is another separate distributed system which comes with costs (though it's pretty cost-effective with Streamkap and we remove all the admin overhead).

Pros - can remove deeply nested sensitive data amongst required useful data.Flink also allows for flexibility around whether it acts like a blocklist or allowlist and alerting around that.

Cons - If Streamkap is deployed as SaaS, data leaves your environment (but is not stored long term), if you have least access policies, it's worth considering that even with BYOC, data is being read out from the source database

More and more folks are asking about masking/dropping CDC data from Postgres before it lands in @Snowflake or other destinations. There are a few options we've seen/enabled Streamkap, each with its pros and cons:

Agentic Analytics Demo Night lands in San Francisco this Wednesday 🚀 We're joining @inngest, @lightdash_devs, and @streamkap for an evening of demos from teams building at the intersection of AI, analytics, and data infrastructure. 🧵

npm install -g @ streamkap/tools @Streamkap CLI is live. Have your agent check it out and tell us what it thinks!

At @Streamkap our customers are ready for the future. Are you? Agents can't make the right decisions without fresh data. Do your customer and operational agents know what's happening now?

Real-time data is the heartbeat of enterprise AI, but traditional pipeline complexity often stalls the pulse. 🫀 @Streamkap brings zero-ops streaming to the Snowflake AI Data Cloud, turning slow batches into instant, contextually relevant AI. ❄️ Build products, not plumbing. Learn more: 👉 bit.ly/4cKhix3

My favorite use case for AI lately? Excalidraw-style architecture diagrams. See a few recent ones attached here. I've been working through a backlog of customer case studies for @Streamkap and wanted visualizations to accompany them. Creating architecture diagrams that show before and after is a pain. I'm not great at it; it would have taken me like an hour per image. Then, I thought, let's see if nano-banana can handle this. Boy, can it ever. @GeminiApp Nano Banana Prompt: "Create an excalidraw style before and after diagram based on this case study." Then paste into the full text of the case study. Make sure you check the nano banana/image creation button.