Key concepts
Storage types
Marple DB is a highly optimised data storage solution. It mainly targets high-frequency time series data obtained with measurement files. To optimise cost and performance, it combines three types of storage in a seamless way:
Hot storage (PostgreSQL)
Cold storage (Parquet on Apache Iceberg)
Archive storage (Object storage)
Marple DB automatically handles loading individual signals from cold storage to hot when needed. Lifecycle rules can be used to transition from cold to archive.
Datastream
Marple DB can consume data from different sources. A datastream allows you to configure
The file plugin (see below)
Preprocessing rules rules
A unified name space (UNS)
Automations
Read more in Datastreams
Plugin
Data files exist in a lot of different file types (CSV, MDF, MAT, HDF5, ...). A plugin is a software module that reads out the data & metadata for a specific file type.
Read more in Supported file types
Datapool
A datastream writes its data into a datapool, which defines the Postgres tables where data will be written to.
By default, all datastreams write into the same default datapool. Changing this is for advanced use cases.
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