Crate aws_sdk_timestreamwriteCopy item path

Amazon Timestream is a fast, scalable, fully managed time-series database service that makes it easy to store and analyze trillions of time-series data points per day. With Timestream, you can easily store and analyze IoT sensor data to derive insights from your IoT applications. You can analyze industrial telemetry to streamline equipment management and maintenance. You can also store and analyze log data and metrics to improve the performance and availability of your applications.

Timestream is built from the ground up to effectively ingest, process, and store time-series data. It organizes data to optimize query processing. It automatically scales based on the volume of data ingested and on the query volume to ensure you receive optimal performance while inserting and querying data. As your data grows over time, Timestream’s adaptive query processing engine spans across storage tiers to provide fast analysis while reducing costs.

§Getting Started

Examples are available for many services and operations, check out the examples folder in GitHub.

The SDK provides one crate per AWS service. You must add Tokio as a dependency within your Rust project to execute asynchronous code. To add aws-sdk-timestreamwrite to your project, add the following to your Cargo.toml file:

[dependencies]
aws-config = { version = "1.1.7", features = ["behavior-version-latest"] }
aws-sdk-timestreamwrite = "1.59.0"
tokio = { version = "1", features = ["full"] }

Then in code, a client can be created with the following:

use aws_sdk_timestreamwrite as timestreamwrite;

#[::tokio::main]
async fn main() -> Result<(), timestreamwrite::Error> {
    let config = aws_config::load_from_env().await;
    // You MUST call `with_endpoint_discovery_enabled` to produce a working client for this service.
    let client = aws_sdk_timestreamwrite::Client::new(&config).with_endpoint_discovery_enabled().await;

    // ... make some calls with the client

    Ok(())
}

See the client documentation for information on what calls can be made, and the inputs and outputs for each of those calls.

§Using the SDK

Until the SDK is released, we will be adding information about using the SDK to the Developer Guide. Feel free to suggest additional sections for the guide by opening an issue and describing what you are trying to do.

§Getting Help

• GitHub discussions - For ideas, RFCs & general questions
• GitHub issues - For bug reports & feature requests
• Generated Docs (latest version)
• Usage examples

§Crate Organization

The entry point for most customers will be Client, which exposes one method for each API offered by Amazon Timestream Write. The return value of each of these methods is a “fluent builder”, where the different inputs for that API are added by builder-style function call chaining, followed by calling send() to get a Future that will result in either a successful output or a SdkError.

Some of these API inputs may be structs or enums to provide more complex structured information. These structs and enums live in types. There are some simpler types for representing data such as date times or binary blobs that live in primitives.

All types required to configure a client via the Config struct live in config.

The operation module has a submodule for every API, and in each submodule is the input, output, and error type for that API, as well as builders to construct each of those.

There is a top-level Error type that encompasses all the errors that the client can return. Any other error type can be converted to this Error type via the From trait.

The other modules within this crate are not required for normal usage.