Running your EL tasks from the CLI has never been simpler. Whether ingesting CSV or JSON files, transferring data between databases, or exporting a custom SQL query to a Parquet file — Sling is the solution that empowers you to achieve it effortlessly.
sling run --src-conn AWS --src-stream s3://file.csv --tgt-conn SNOWFLAKE --tgt-object my_schema.my_table
sling run --src-conn CLICKHOUSE --src-stream default.my_table --tgt-conn PG --tgt-object my_schema.my_table
cat my_file.csv | sling run --tgt-conn MYDB --tgt-object my_schema.my_table
Core engine is written in Go and adopts a streaming design, making it super efficient by holding minimal data in memory
Easily replicate data from a source database, file or SaaS connection to a destination database or file. Define the configuration in a YAML file.
Sling allows you to run your own operation in whatever environment you prefer.
With the list sub-command, we can display all connections available from our Sling Env File as well as Environment Variable. Oh, are your using dbt profiles? Sling picks those up too!
The Sling CLI tool also allows testing connections. Once we know the connection name, we can use the sling conns test command.
The discover sub-command displays which streams are available for sling is read from for a particular connection. You can even filter by schema for database connections, or by folder for storage connections.
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You can easily define your replications in YAML files. You're able to specify default values as well as naming patterns! Check the docs here for more details.
Mac:
brew install slingdata-io/sling/sling
Windows:
scoop bucket add sling https://github.com/slingdata-io/scoop-sling.git
scoop install sling
Linux:
curl -LO 'https://github.com/slingdata-io/sling-cli/releases/latest/download/sling_linux_amd64.tar.gz' \
&& tar xf sling_linux_amd64.tar.gz \
&& rm -f sling_linux_amd64.tar.gz \
&& chmod +x sling
Docker:
docker pull slingdata/sling
docker run --rm -i slingdata/sling --help
Python:
pip install sling
More:
See Github Repository.
For any additional questions, feel free to send a message here .
Many connection types are supported including MySQL, Oracle, Postgres, SQL Server, AWS S3, Google File Storage, Azure Storage, SFTP and more. See here for a complete list.
Yes it is! Just install it on your machine and use it as you wish. No strings attached. The github repository is located here.
