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by noahfschr 1897 days ago
I will be happy if someone from Fauna team helps me to improve my code. https://github.com/upstash/latency-comparison

Upstash is not non-durable. It is based on multitier storage (memory + EBS) implementing Redis API. In a few weeks, I will add upstash premium which replicates data to multiple zones, to the benchmark app.

In the blog post, I mentioned the qualities where Fauna is stronger than the others: https://blog.upstash.com/latency-comparison#why-is-faunadb-s...
1 comments
evanweaver 1897 days ago
Your own docs say that by default “writes are not guaranteed to be durable even if the client receives a success response”.
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noahfschr 1897 days ago
Upstash has two consistency modes. Eventual consistency and Strong consistency. Please see: https://docs.upstash.com/overall/consistency

In my code, Upstash database was eventually consistent. Similarly the index in the FaunaDB was not serialized.

But both of those should not affect the latency numbers in the histogram because those numbers are all read latency.

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rbranson 1897 days ago
That's an apples to oranges comparison though. Upstash couples durability with consistency/isolation. Regardless of configuration, FaunaDB and DynamoDB both always ensure durability of acknowledged writes with a fault tolerance of greater than 1 node failure. To compare them on equal footing, Upstash would need to be configured for strong consistency, at least according to the docs.
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ec109685 1897 days ago
DynamoDB also guarantees your write is distributed to multiple data centers as well.
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evanweaver 1897 days ago
No it doesn't. The write is not durable in other datacenters when the client acknowledgement is returned. It is still possible to lose data.
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rbranson 1897 days ago
It does. The three AZs they replicate across are just as good as anything else someone typically calls a "datacenter." Amazon itself operates retail out of one region and uses multi-AZ as a fault tolerance strategy.
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ec109685 1897 days ago
It won’t lose data in the event of a data center failure. Each of the replicas is in a different AZ, and at least two of three have to durably write the data before the put succeeds.
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