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distributedsystems: All content tagged as distributedsystems in NoSQL databases and polyglot persistence

Scalable Atomic Visibility with RAMP Transactions

We’ve developed three new algorithms—called Read Atomic Multi-Partition (RAMP) Transactions—for ensuring atomic visibility in partitioned (sharded) databases: either all of a transaction’s updates are observed, or none are.

Still digesting Peter Bailis’s post and the accompanying Scalable Atomic Visibility with RAMP Transactions paper.

Original title and link: Scalable Atomic Visibility with RAMP Transactions (NoSQL database©myNoSQL)


Concurrent updates, distributed systems and clocks, vector clocks, last-write-win, and CRDT

Great post by John Daily from Basho about concurrent updates in the world of distributed systems and the implications of using clocks, vector clocks, last-write-wins, distributed data types (Commutative Replicated Data Type):

The problem is simple: there is no reliable definition of “last write”; because system clocks across multiple servers are going to drift.

Original title and link: Concurrent updates, distributed systems and clocks, vector clocks, last-write-win, and CRDT (NoSQL database©myNoSQL)


The "network partitions are rare" fallacy

Kelly Sommers:

Partitions in distributed systems is about availability not about network infrastructure. Many things can cause a node to be unavailable to a segment of other nodes.

Original title and link: The “network partitions are rare” fallacy (NoSQL database©myNoSQL)


The demise of eventual consistency?

A well written article by FoundationDB’s founder Dave Rosenthal about eventual consistency:

The concept of eventual consistency comes up frequently in the context of distributed databases. Leading NoSQL databases like Riak, Couchbase, and DynamoDB provide client applications with a guarantee of “eventual consistency”. Others, like MongoDB and Cassandra are eventually consistent in some configurations.

I could ignore some smart word choices and agree that dealing with eventual consistency is not a familiar area to many developers.

What I cannot agree with though, are weak statements like (what does unreliable writes mean?) :

Eventual consistency pushes the pain and confusion of inconsistent reads and unreliable writes onto software developers.

And definitely I cannot agree with unproved statements used solely to prove your point:

A system that keeps some, but not all, of its nodes able to read and write during a partition is not available in the CAP sense but is still available in the sense that clients can talk to the nodes that are still connected. In this way fault-tolerant databases with no single point of failure can be built without resorting to eventual consistency.

By changing the definitions, you are not proving a theorem is incorrect. Nor do you prove a different theorem.

Original title and link: The demise of eventual consistency? (NoSQL database©myNoSQL)