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Netflix
dynomite
C2014–2024
Netflix / dynomite

dynomite

A generic dynamo implementation for different k-v storage engines

14Distinct people
17Mentions
0Explicit recommenders
4.2KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

A generic dynamo implementation for different k-v storage engines

GitHub

Where it is used

No documented product use was verified in the last source check.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

Mentioned in the same Hacker News threads. That is not proof they are substitutes.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:56:07 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year17 dated mentions

Observed mentions: 2014-11-03 22:07:16 UTC to 2024-03-29 15:25:16 UTC.

0123452014-01-01 00:00:00 UTC to 2015-01-01 00:00:00 UTC (exclusive): 4 mentions; 0 submissions, 4 comments20142015-01-01 00:00:00 UTC to 2016-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2016-01-01 00:00:00 UTC to 2017-01-01 00:00:00 UTC (exclusive): 5 mentions; 1 submissions, 4 comments2017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20192020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2024

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20142014-01-01 00:00:00 UTC2015-01-01 00:00:00 UTC404
20152015-01-01 00:00:00 UTC2016-01-01 00:00:00 UTC101
20162016-01-01 00:00:00 UTC2017-01-01 00:00:00 UTC514
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC202
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC000
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC101
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC101
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC101
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC101
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC000
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC101

What Hacker News says

17 sources
I thought you'd never ask: - KeyDB (https://keydb.dev) - Pelican Cache (https://www.pelikan.io/) - Tendis (https://github.com/Tencent/Tendis) - SSDB (https://github.com/ideawu/ssdb) - Dynomite (https://github.com/Netflix/dynomite/) - Dragonfly (https://github.com/dragonflydb/dragonfly) - Skytable (https://github.com/skytable/skytable) - Tidis (https://github.com/yongman/tidis) - Anna (https://github.com/hydro-project/anna) - Skyhook (https://github.com/aerospike/skyhook) And some which are kinda dead but still interesting -- redis is the kind of workload that does actually become feature complete so these are still usable in my mind though maybe not first choice: - ledisdb (https://github.com/ledisdb/ledisdb) - Codis (https://github.com/CodisLabs/codis) - xcodis (https://github.com/ledisdb/xcodis) I'm planning on doing a comparison with t
Read the rest
hese at some point, because they're fascinating (all these projects go off in subtly different directions, I'll spare you the details), but here's a recent comparison someone else did: https://news.ycombinator.com/item?id=31796311 Basically, redis compatibility is like step 1 for any KVS that wants to seem at least a little usable/real-world-focused so you get so many cool entrants. I don't really personally keep up with redis for the stream use-case -- it's a great use for redis but that doesn't really make/break for me usually.
In I deleted 78% of my Redis container and it still works
Does anyone have any experience with these other Redis clones? I need to write a benchmark on these someday (the outline for the blog post is already written), but have restricted my yak shaving recently: - https://github.com/Tencent/Tendis - https://github.com/Netflix/dynomite On a separate note, was FLASH (as in "flash memory") supposed to be an acronym? I've never seen people treat it as an acronym before.
In KeyDB CEO Interview: Getting into YC with a Fork of Redis
> I'm just waiting for the day they can make the database immutable. It'll probably look something like git. Netflix had immutable databases back in 2012. I mean, as close as you can get I suppose. We could lose 1/3 of the nodes and keep running normally, and lose 2/3 and keep reading. It was built with Cassandra and based on the Dynamo model. There was also an open source, fully in memory database with the same reliability: https://github.com/Netflix/dynomite
In Erase your darlings: immutable infrastructure for mutable systems
Following research papers from academia also explored similar problem: 1) BESPOKV: Application Tailored Scale-Out Key-Value Stores http://people.cs.vt.edu/~butta/docs/sc18-bespokv.pdf 2) ClusterOn: Building Highly Configurable and Reusable Clustered Data Services using Simple Data Nodes http://people.cs.vt.edu/~butta/docs/hotstorage16-clusteron.p... DynomiteDB from Netflix allowed to scale singe server NoSQL stores. https://github.com/Netflix/dynomite.
In Technical Challenges Developing a Distributed SQL Database
twemproxy is not the best piece of software when it comes to maintenance of code quality. But it works reliable. We are still using twemproxy and we are maintaining our own fork of it. This fork often has changes from us, like bugfixes or introducing new redis commands that are not supported yet. Every bug we fix we apply this as a PR. A few PRs from the repository we have cherry-picked internally and deployed. But we have also a few issues with it like this one here: https://github.com/twitter/twemproxy/issues/442 or live reconfiguration would be a nice feature. Think about it if you really need this, because it is not only fun. A few pain points: * Deployments of new configs and restarting twemproxy on your server farm * New redis version with new commands? Extend twemproxy for those command support I don't now any _real_ alternative to
Read the rest
it, right now. I know from https://github.com/Netflix/dynomite which is a twemproxy fork. When we had only memcached and no redis (we are using both with twemproxy), then we would try https://github.com/facebook/mcrouter from facebook. But it is specialized on memcached. If you come up with an alternative, please let me know.
In Learn Redis the hard way: in production
https://github.com/Netflix/dynomite Dynomite for production proven, limitless scale for Redis. Provides ability to Redis for both in-memory and on-disk workloads. Dynamo-inspired linearly scalable, shared nothing multi-master architecture. Pairs well with Cassandra. Supports pluggable backends (ex. RocksDB). Been in production 2+ years. One of the larger clusters handles over 3.6 million sustained ops/sec in production, every day.
In Show HN: SummitDB – In-Memory NoSQL DB

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