Blob Store
Blob=binary large object, is a mass of data in binary form that does not necessarily conform to any file format.
Blob storage is a type of cloud storage for large amount of unstructured data: documents, images, audio, and video.
Pros: Blob storage is scalable, durable, and highly available with built-in redundancy.
Blob storage is designed for:
- Serving images or documents directly to a browser
- Storing files for distributed access
- Streaming video and audio
- Writing to log files
- Storing data for backup and restore, disaster recovery, and archiving
- Can be accessed via HTTP
Example db: AWS S3, Google Cloud Storage.
Time Series DB
Time series database is optimized for storing and querying time-stamped data.
Time series data is data that is collected and stored over time, typically at regular intervals.
Pros: efficient querying of data over a time range, fast ingestion of new data.
Usage example: monitoring tools, financial applications, where it is important to store and analyze historical data about stock prices and other financial data.
Example db: Prometheus, InfluxDB.
Graph DB
A graph database is a type of database that stores data in the form of a graph, rather than in a tabular form.
Data is organized as a set of nodes and edges.
- Each node representing an entity (such as a person or a business).
- Each edge representing a relationship between two nodes (such as a friendship or a business partnership).
Graph databases are optimized for storing and querying relationships between entities.
Pros: They provide fast lookup of data based on the connections between entities and are useful for applications that need to query complex relationships between data.
Usage examples: social networking platforms, recommendation engines, and fraud detection systems.
Spatial DB
Geometric locations, locations on map (latitude and longitude).
Spatial database is optimized for storing and querying spatial data/relationship, which is data that represents the position and shape of objects in space.
Spatial data can be used to represent the locations of physical objects, such as buildings, roads, and land parcels, as well as abstract concepts such as electoral districts or wireless network coverage areas.
Some examples of spatial relationships include proximity (e.g., "find all points within a certain distance of a given location"), containment (e.g., "find all points that are contained within a given polygon"), and intersection (e.g., "find all lines that intersect with a given polygon").
Example applications: geographic information systems (GIS), transportation planning, and location-based services. Geology, archaeology, and meteorology, where it is important to analyze and visualize spatial data.
