Keep all your Data organized and available in real time, 24/7.
Collect data from any existing system and organize it according to your business needs. Build a single point of truth to keep your data flow consistent and updated in real-time 24/7.
Fast Data main goal is to aggregate business data from different sources into a single MongoDB collection called single view. These collections can be easily queried by your APIs. The aggregation is performed only when needed, that is when changes occur to the source data.
Focus only on your data and how you need to aggregate them, your single views will be automatically updated.
In this section, you can have an overview of the components and the processes of Fast Data. You can easily configure Fast Data directly from the Console.
You need to implement a service able to send to Kafka any change in your original sources of data happens. From now on, we will call the sources Systems of Records.
You can implement it however you want.
The Real-Time Updater component consumes Kafka messages and is in charge of keeping the projections collections up to date with the systems. For each System you create, a new real-time updater is automatically created (please note that they are not visible in the
Each source system table that contains data linked to a single view will have a projection collection. These collections contain the standardized values of the fields of the related system table. This set of collections will be used from the Single View Creator to update the single view collections.
In order to know which single view needs to be updated, the Single View Creator periodically reads a collection named
fast-data-projections-changes which contains all the info it needs. To gather these data we need to define one strategy for each projection, because when the projection is affected by a change we need to calculate which single views are impacted. This is made possible by the
For instance if we have a table A that when modified impacts the tables B and C, when receiving a change on table A we need to calculate also the impacted rows on table B and table C and all the single views that depend on them.
The Single View Creator component creates and updates a specific single view.
First, the Single View Creator aggregate data of projections, then maps these values to an object with the correct single view fields. Finally, updates the single view collection.