10 million records. Assume 250 bytes per record. That is about 2.5 Gb of data, which is well within the capacity of a basic desktop / laptop PC.
The data volumes are insignificant (unless each record is sized in Mb, such as picture or audio).
10 million records. Assume 250 bytes per record. That is about 2.5 Gb of data, which is well within the capacity of a basic desktop / laptop PC.
The data volumes are insignificant (unless each record is sized in Mb, such as picture or audio). What you do need to talk about is transaction volumes (separated into read and write) and what you consider HA. Read-only HA is easy relative to "Read-write HA".
It can be trivial to replicate a read-only data set off to multiple servers at different geographic locations and distribute a query workload on them. It's much harder to scale out an update heavy workload, which is why you often hear about systems going into meltdown when tickets for a big concert are released. Quite simply there's a fixed number of seats and you can't have ten duplicated systems each selling what they think is available.
There has to be a single source of truth, which means a bottleneck (and potentially a single point of failure). On the HA aspect, RAC is a shared storage technology which generally means your RAC nodes are in close proximity. That can make them vulnerable to localized events such as a building fire or telecoms breakdown.
Data Guard is the Oracle technology that relates to off-site replication and failover.
10 milion records, but they expected to grow 30-50% every two week. I wonder at what moment Oracle will be getting slower? I am trying to find any benchmarks if we are going to use Oracle RAC as key-value storage comparing to Cassandra/MongoDB/etc.Who provides better perfomance?
I am more interested in reads; – alexeypro Feb 10 at 17:29.
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