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Workflow
re-startable monad that recover the execution state from a log, and workflow patterns (by agocorona)
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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plumber
A swiss army knife CLI tool for interacting with Kafka, RabbitMQ and other messaging systems.
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
I was part of that debate, I remember a rather interesting point of discussion: Is the main operation "apply" or "dedup"
Apply seems to be the common notion of event sourcing: There is a function apply that takes a state an event and yields a new state. Then, starting in an init state and iteratively applying the entire event history, boom, latest state restored.
Dedup has a lot of charm though: Run and rerun your code, if that step of your code is executed for the first time (no corresponding event in the event history) execute the step and store its result as an event in the history, however, if that step of your code is executed for the second, third time (there is a corresponding event in the event history) do not execute the step and return its result from the event in the history. The Haskell Workflow Package (https://hackage.haskell.org/package/Workflow) is a good example
Temporal follows the second approach, so "proper" Event Sourcing? You be the judge :)
I recently built https://github.com/siriusastrebe/jsynchronous which uses event sourcing to synchronize javascript variables on the server with connected browsers.
You can also replay states using a special “rewind” mode, a core advantage of event sourcing.
Last time i looked into it there weren't that many i could find. There is https://github.com/tikv/tikv which uses rocksdb with raft. and there is faster https://github.com/microsoft/FASTER/ .
Last time i looked into it there weren't that many i could find. There is https://github.com/tikv/tikv which uses rocksdb with raft. and there is faster https://github.com/microsoft/FASTER/ .
Check out MessageDB https://github.com/message-db/message-db. It's basically Postgres and can be installed into any Postgres DB.
Hi there, I started a company specifically centered around event sourcing - it's a saas platform for capturing all of your events, gaining the ability to granularly search them and then replay them to whatever destination.
I'd be happy to walk you through the platform - there's no lock-in, since we don't require the use of any SDK's, just run an event-relaying container which will pipe all of your events to our stores.
One big piece is that our platform is message bus agnostic meaning, we are able to hook into any message bus, be it kafka, rabbit, nats, etc.; same goes for replays - we can replay into any destination.
Check it out: https://batch.sh
The relayer is open source - https://github.com/batchcorp/plumber - if anything, the relayer can also be used for working with message busses which could improve your dev workflow for reading/writing messages, etc.
Sure - here's a simple fuzzer from a rope (fancy string) library I wrote a few years ago back when I was still learning rust. (Don't judge me!):
https://github.com/josephg/skiplistrs/blob/master/tests/test...
In a loop it simply randomly decides whether to insert, delete or replace some text, and after any action checks that the state is valid (In this case via a call to check2()).
You can go way deeper with this sort of thing if you want, with more complex models, random item generation and simplifiers to help pare down problems to simple test cases. And you can have more complex state - for example, where you also track interaction between multiple items. For example, if your state is a few users, and you also track one user paying another user and verify the total balance across all users is unchanged.
But you don't need to go deep for fuzz testing to be worthwhile. Even something as simple as this little loop is a remarkably effective bug finder.