Documentation Index
Fetch the complete documentation index at: https://docs.activeviam.com/llms.txt
Use this file to discover all available pages before exploring further.
Some Atoti features require large additional libraries and might not be useful in every projects.
To keep the core library as light as possible, these features are packaged into separate plugins that can be installed when needed.
Available plugins
Data loading
atoti_jdbc | Code to interact with databases through JDBC. |
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atoti_kafka | Code to interact with Kafka streams. |
atoti_parquet | Code to load Apache Parquet files. |
Cloud storage
atoti_storage_aws | Code to load CSV and Parquet files from AWS S3 into Atoti tables. |
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atoti_storage_azure | Code to load CSV and Parquet files from Azure Blob Storage into Atoti tables. |
atoti_storage_gcp | Code to load CSV and parquet files from Google Cloud Storage into Atoti tables. |
- Bandwidth of the network interface.
- Speed of the CPU cores since HTTPS connections and client side-encryption consume CPU resources.
- File size: small files will not have good download speed (< 60 MB/s).
- Type (hot/cold) of the storage: hot storage is faster.
- Data locality: best when the host running Atoti and the data are in the same cloud region.
DirectQuery
See Using DirectQuery.
Administration & Monitoring
atoti_observability | Plugin enhancing observability of Atoti sessions. |
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atoti_spring_boot_admin | Plugin enabling Spring Boot Admin. |
Installation
A plugin can be installed as a Python package or as a Conda package.
For instance, to install the DirectQuery JDBC plugin:
Python package (recommended)
With uv:
uv add "atoti[directquery-jdbc]"
pip install "atoti[directquery-jdbc]"
uv add "atoti[directquery-jdbc,jupyterlab,spring-boot-admin]"
Conda package (discouraged)
conda install atoti atoti-client-directquery-jdbc atoti-server-directquery-jdbc
