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I'm not sure if it should be plural when referring to the technology in general. "Powered by blockchains technology" doesn't seem correct to me.

I do hope you'll read the article regardless!

I probably should not be capitalizing it ever and using it as singular everywhere. Thanks for pointing that out

It is interesting how Go seems to be doomed to head down the same path as other languages it accused of being "bloated." No one intends to design a complicated language but the reality is that the problem space is complicated.

The only thing that isn't so forgivable with Go is that these aren't new problems this time around. Go is still struggling to get over challenges that were first seen a long time ago. It's a great experiment on designing for complexity vs trying to avoiding complexity.

Yes microbatching is a great way to get a fixed write rate regardless of traffic, can even do it right at the application layer. The trade-off is that you can theoretically lose one interval of data when your service goes down. This might not matter for analytics workloads with a margin of error but some usecases require confirmed writes

There are a few misguided views in this article and in some of these comments.

1. Every shardable database (Cassandra, Dynamo, BigTable) has to worry about hot spots. Picking a UUID as a partition key is only step one. What happens if one user is a huge majority of your traffic? All of their reads/writes are going to a single partition and of course you are going to suffer from performance issues from that hot spot. It becomes important to further break down your partition into synthetic shards or break up your data by time (only keep a day of data per shard). BigTable does not innately solve this, they may deal better with a large partition but it will inevitably become a problem.

2. Some people are criticizing the choice of NoSQL citing the data size. Note you can have a small data size but have huge write traffic. An unsharded RDBMS will not scale well to this since you cannot distribute the writes across multiple nodes. Don't assume just because someone has a small data set they don't need to use NoSQL to deal with their volume

Great advice to everyone, not just self-learners

Yeah I don't get why they're marketing to Mongo users, weird choice. This is a DB for companies trying to moved to a query-less architecture - something no one should be doing with mongo

Cross datacenter replication is the missing piece from AWS. I wish they'd just roll out a hosted Cassandra or something identical

Implementing aggregation at query time is a temporary solution. For systems like this aggregation should be done on insert time - many hugely popular databases do not provide much more than a basic get operation for this reason

Databases in this category are some of the most popular ones in the world with good reason. The only way you can scale is to adopt a query-free architecture.

It feels tedious at first but once you develop some good habits and frameworks around denormalization it becomes easy to do that from day one.