Event storage is continuous, infinite, durable and eventually consistent. It is not limited to Backup/IoT traffic but it is different from applications requiring object storage. As object storage makes inwards into vectorized execution, the data transfers become increasingly fragmented and continuous. At this junction it is important to facilitate data transfer between objects and streams
Since Event storage overlays on Tier 2 storage on top of blocks, files and blobs, it is already transferring data to object storage. However, the reverse is not that frequent although objects in a storage class can continue to be serialized to Event in a continuous manner. It is also symbiotic to audience on both storage.
Although stream storage is best for events, any time-series database could also work. However, they are not web-accessible unless they are in an object store. Their need for storage is not very different from applications requiring object storage that facilitate store and access. However as object storage makes inwards into vectorized execution, the data transfers become increasingly fragmented and continuous. At this junction it is important to facilitate data transfer between objects and streams and it is in this space that Events and object store find suitability. Search, browse and query operations are facilitated in a web service using a web-accessible store.
Time Series Database offers a viable option as an Event store. For example, InfluxDB is used to record Sensor data and Grafana stack is used to make charts and graphs for dashboards using the same data. Most of these time-series databases are also deployed using clusters and typically represent the growing trend towards this kind of Big Data and search-based analytics.
Moreover, not all the requests need to reach the object storage. In some cases, web Time Series Database may use temporary storage from hybrid choices. The benefits of using a web Time Series Database including saving bandwidth, reducing server load, and improving request-response time. If a dedicated content store is required, typically the storage and server are encapsulated into a content server. This is quite the opposite paradigm of using object storage and replicated objects to directly serve the content from the store. The distinction here is that there are two layers of functions - The first layer is the Time Series Database that solves read-only distribution using techniques such as governing, asset copying and load balancers. The second layer is the compute and storage bundling in the form of a server or a store with shifting emphasis on compute and storage.
Since Event storage overlays on Tier 2 storage on top of blocks, files and blobs, it is already transferring data to object storage. However, the reverse is not that frequent although objects in a storage class can continue to be serialized to Event in a continuous manner. It is also symbiotic to audience on both storage.
Although stream storage is best for events, any time-series database could also work. However, they are not web-accessible unless they are in an object store. Their need for storage is not very different from applications requiring object storage that facilitate store and access. However as object storage makes inwards into vectorized execution, the data transfers become increasingly fragmented and continuous. At this junction it is important to facilitate data transfer between objects and streams and it is in this space that Events and object store find suitability. Search, browse and query operations are facilitated in a web service using a web-accessible store.
Time Series Database offers a viable option as an Event store. For example, InfluxDB is used to record Sensor data and Grafana stack is used to make charts and graphs for dashboards using the same data. Most of these time-series databases are also deployed using clusters and typically represent the growing trend towards this kind of Big Data and search-based analytics.
Moreover, not all the requests need to reach the object storage. In some cases, web Time Series Database may use temporary storage from hybrid choices. The benefits of using a web Time Series Database including saving bandwidth, reducing server load, and improving request-response time. If a dedicated content store is required, typically the storage and server are encapsulated into a content server. This is quite the opposite paradigm of using object storage and replicated objects to directly serve the content from the store. The distinction here is that there are two layers of functions - The first layer is the Time Series Database that solves read-only distribution using techniques such as governing, asset copying and load balancers. The second layer is the compute and storage bundling in the form of a server or a store with shifting emphasis on compute and storage.
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