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  1. neon.techNeon Serverless Postgres — Ship faster

    Neon is a fully managed serverless Postgres service that offers autoscaling, branching, and bottomless storage. It is designed for developers and partners who need scalable, cost efficient, and easy to use Postgres databases.

  2. github.com › neondatabase › neonGitHub - neondatabase/neon: Neon: Serverless Postgres. We ...

    • Neon
    • Quick start
    • Architecture overview
    • Running local installation
    • Running tests
    • Flamegraphs
    • Documentation
    • Join the development
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    Neon is a serverless open-source alternative to AWS Aurora Postgres. It separates storage and compute and substitutes the PostgreSQL storage layer by redistributing data across a cluster of nodes.

    See full list on github.com

    Try the Neon Free Tier to create a serverless Postgres instance. Then connect to it with your preferred Postgres client (psql, dbeaver, etc) or use the online SQL Editor. See Connect from any application for connection instructions.

    Alternatively, compile and run the project locally.

    See full list on github.com

    A Neon installation consists of compute nodes and the Neon storage engine. Compute nodes are stateless PostgreSQL nodes backed by the Neon storage engine.

    The Neon storage engine consists of two major components:

    •Pageserver: Scalable storage backend for the compute nodes.

    •Safekeepers: The safekeepers form a redundant WAL service that received WAL from the compute node, and stores it durably until it has been processed by the pageserver and uploaded to cloud storage.

    See full list on github.com

    Installing dependencies on Linux

    1.Install build dependencies and other applicable packages

    •On Ubuntu or Debian, this set of packages should be sufficient to build the code:

    •On Fedora, these packages are needed:

    •On Arch based systems, these packages are needed:

    Building Neon requires 3.15+ version of protoc (protobuf-compiler). If your distribution provides an older version, you can install a newer version from here.

    See full list on github.com

    Ensure your dependencies are installed as described here.

    By default, this runs both debug and release modes, and all supported postgres versions. When testing locally, it is convenient to run just one set of permutations, like this:

    See full list on github.com

    You may find yourself in need of flamegraphs for software in this repository. You can use flamegraph-rs or the original flamegraph.pl. Your choice!

    Important

    See full list on github.com

    docs Contains a top-level overview of all available markdown documentation.

    •sourcetree.md contains overview of source tree layout.

    To view your rustdoc documentation in a browser, try running cargo doc --no-deps --open

    See also README files in some source directories, and rustdoc style documentation comments.

    Other resources:

    •SELECT 'Hello, World': Blog post by Nikita Shamgunov on the high level architecture

    See full list on github.com

    •Read CONTRIBUTING.md to learn about project code style and practices.

    •To get familiar with a source tree layout, use sourcetree.md.

    See full list on github.com

    Neon is an open-source alternative to AWS Aurora Postgres that separates storage and compute. Learn how to install, run, and connect to Neon locally or on the cloud.

    See full list on github.com

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  4. neon.tech › docs › manageManage databases - Neon Docs

    Jan 8, 2024 · Learn how to create, view, update, and delete databases in Neon, a PostgreSQL-compatible cloud database service. Neon supports managing databases from the console, CLI, and API interfaces.

  5. neon.tech › docs › get-started-with-neonWhy Neon? - Neon Docs

    In summary, Neon is built for anyone who requires a Postgres database and wants to benefit from the scalability, ease of use, cost savings, and advanced DevX capabilities provided by Neon's serverless architecture. Neon makes it easy to get started with Postgres. Set up your Postgres database in seconds.

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