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Feldera on Ubuntu 24.04 | cloudimg

durch cloudimg

Streaming SQL and incremental view maintenance engine with a Web Console

Feldera is an open source incremental compute engine for continuous analytics over data in motion. You write ordinary SQL, a table and a view over it, and Feldera compiles the program into a running pipeline that keeps the view's results correct as rows are inserted, updated and deleted, doing only the work each change requires instead of recomputing from scratch.

This cloudimg image ships the MIT licensed Feldera open source edition, the all in one pipeline manager (REST API, Web Console, SQL to native compiler and local runner) pointed at a bundled PostgreSQL 16 database for metadata, run the officially supported way as an upstream container orchestrated by Docker Compose under systemd on Ubuntu 24.04 LTS. Both images are pinned by digest and captured into the VM, so your instance starts without pulling anything. The pipeline manager and the bundled PostgreSQL are bound to the loopback interface only; PostgreSQL is never exposed on a host port.

Feldera's open source build has no built in authentication, so cloudimg fronts the Console and REST API with nginx HTTP Basic Auth using a unique bcrypt password generated automatically the first time your VM boots, before the port is reachable, and recorded in a root only file. No default or shared credential ever ships. A unique database password is generated the same way, an eight gigabyte swap file is provisioned so the runtime SQL to native compiler has headroom, and the metadata database starts freshly initialised with no prior pipelines.

The cloudimg charge covers packaging, security patching, image maintenance and 24/7 expert support. Feldera is licensed under the permissive MIT license and is free to use. Build and run streaming SQL pipelines from the Web Console, query materialized views on demand, and watch changes flow through in real time. Because pipelines compile to native code, a larger size such as Standard_D4s_v3 is recommended for production. See the deployment guide for the full walkthrough.

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