- There is a one to one correspondence between formatting data and data modeling. For every model of data, there is only one way to store the data.
- There is always one specific schema for storing model data that is the best and preferred method for the specific data representation.
- The data does not necessarily need to be formatted in a way that represents the data model. Just so long as it can be extrapolated.
- Calculating results using real time data otherwise known as streaming data.
- Using static data stored from a real time source in order to process and guide the application.
- Utilizing real time data to compute and change the state of an application continuously.
- Using sensors to manipulate the system, such as a smart car being able to drive by itself using sensors to detect road hazards.
- Small time windows for working with data.
- Data is always utilized for streaming the application.
- Data manipulation is near real time.
- Independent computations that do not rely on previous or future data.
- Always unbounded in sequence, in other words, data is not guaranteed to be in order.
- Does not ping the source interactively for a response upon receiving the data.
- Data is unbounded in size but requires only finite time and space to process it.
- The data is unbounded in size and the size determines the time and space of processing the data.
- The data is finite and requires only finite time and space to process the data.
- Data is finite in size and size determines the time and space of processing the data.
- Accurate and Consistent
- Accurate and Memory Efficient
- Fast and Complex
- Fast and Simple
- A specific method for processing streaming data using special real time processes.
- A specific hardware architecture for a server made specifically for processing real time data.
- A method to process streaming data by utilizing batch processing and real time processing.
- The size and frequency of the streaming data may be too small.
- The size and frequency of the streaming data may be sporadic.
- There may not be data to produce the notion of size and frequency.
- Data lakes house raw data while data warehouses contain pre-formatted data.
- Data lakes contain only files while data warehouses contain only databases.
- Data lakes utilize hierarchical systems while data warehouses use object storage.
- The process where formatted data is given structure when read.
- Another name for data lakes.
- Data is stored as raw data until it is read by an application where the application assigns structure.
- The process where data is pre-formatted prior to being read but the schema is loaded on read.