YouTrackDB is a general-use object-oriented graph database

by gjvc • 9 days ago

174 69 9 days ago

I wonder if there's a design decision documented somewhere that makes the existing graph databases like Neo4j, etc. not good enough for Youtrack's use case.

zihotki• 9 days ago

That's a good question indeed. Also I wonder why they picked java as the implementation language.

rednb• 9 days ago

Likely because they are a Java shop. All the IDEs they develop use Java, so they have quite an expertise in low level optimization for this language.

fsuts2• 9 days ago

Date of commits shows this project is 3 years old.

It’s JetBrains who were synonymous with Java so not a surprise, if was a recent project would have been Kotlin (which this company created)

ChrisRR• 9 days ago

Because Youtrack itself is written in java

pandoro• 9 days ago

Neo4j is a great DB but their license price is egregious for enterprise customers. A few years ago I was involved in negotiating a contract for a small/medium size kubernetes deployment (think around 25 cores) and the annual price was more than the salary of a senior SWE full-time equivalent. See this page for an idea of their prices in 2018: https://blog.igovsol.com/2018/01/10/Neo4j-Commercial-Prices....

brabel• 9 days ago

Also embedding Neo4j is not possible, that seems to be the killer feature for YouTrackDB, they even shade dependencies so it’s like a no deps Java library for your application.

danpalmer• 9 days ago

small/medium size kubernetes deployment (think around 25 cores

That's ~1 machine. 1 SWE for a database isn't egregious, databases provide huge value, but for that little performance, that's crazy.

I can only assume as core count has blown up over the last 10 years, the pricing has somewhat diminished, but still, I'd be expecting a heck of a lot more capacity for 1 SWE.

fsuts2• 9 days ago

Not just that, if a database company has both a community edition and enterprise then it’s likely the enterprise will get many new features that the community edition will never get.

Ongoing enshittification risk.

adsharma4• 8 days ago

There are several MIT/Apache licensed embedded graph databases available, including the one linked from my profile.

denismi• 9 days ago

Didn't Neo4J pivot away from being a boring embedded DB which you point at a path and then traverse through Node objects, and decide to become some kind of paid platform with a client-server protocol and proprietary query DSL?

I remembered it from a uni course (early 10s?) a few years ago for a use-case we didn't end up pursuing, but I wasn't hugely comfortable with investing effort into what I saw.

ajhenrydev• 9 days ago

Do they have a doc that says what scale this can operate at?

winrid2• 9 days ago

It's embedded. Single machine. But it runs their forum/ticketing thing so good enough for that I guess :)

td2• 9 days ago

Isnt youtrackdb a odd name, if its intended as a general use db? Why link it that much to a specific known product?

p_l• 9 days ago

It was split from youtrack internals, IIRC

root3• 8 days ago

current name is smelling tho +1

gjvc3• 8 days ago

use the existing one then (which is actually battle-tested) https://github.com/JetBrains/xodus

gjvc3• 9 days ago

ggcr• 9 days ago

It's a fork of OrientDB, isn't it?

jacolbj• 9 days ago

A successor to it, yes: https://medium.com/@youtrackdb/long-road-ahead-6d648141a190

brobdingnagians• 9 days ago

I've always been curious about graph DBs and dabbled a bit in them, but for those who have more extensive experience in them-- are they really worth it? Is it that for small scale SQL is better and graph DBs really only matter at scale, or for specific use cases with highly connected data?

ChicagoDave• 9 days ago

I played around with Neo4j and only ever found two domains where it excelled.

- custom app security

- social media

I also think cypher is a brilliant way to query a graph.

shaism• 9 days ago

I worked in a startup whose value proposition was largely derived from using graph data and graph databases under the hood. The main benefit is, as the repo even states "Fast data processing: Links traversal is processed with O(1) complexity."

So, technically, you can do deep traversals quicker. A few notes:

1. Few use cases truly need low-latency deep traversal on realtime data (>5 hops). There are some well known ones like fraud detection in payment processing and, possibly, social media recommendation engines. But I am not even sure how latest social media engines work, and whether they still rely on graph DBs.

2. However, in practice the advantage is often marginal. With modern analytical databases, or even an optimized PostgreSQL (ltree, materialized views, pgrouting, pg_duckdb, etc), you often get more than good enough performance. In addition those traditional SQL DBs scale with hardware more easily than graph databases. So, you can always use the lever: "Throw more hardware at it."

3. Even Graph DBs don't get good traversal performance under all conditions without hand tuning. For example, there is the "super node" issue, a node with an abnormally high number of connections (edges). And if you still need hand-tuning, you might as well choose something more versatile.

4. The ecosystem of a PostgreSQL and other popular DBs is just unbeaten. With graph DBs, you often prematurely put yourself in a corner that you don't want to be in.

Hence, my recommendation. Unless you are really sure that a graph DB is the right fit for your use case, start with something else, and go the graph db way when you have established a true need.

snapetom• 9 days ago

I worked for the research branch of a children's hospital. At one point, I was brought into vendor evaluations a department wanted to buy. Their tool had something to do with visualizing protein interactions, which was highly networked. It was basically a Neo4j database with a React UI on top of it.

codelikeawolf• 9 days ago

I'm a bit of a Forensic Files nerd, so I worked on a little side project a while back to pull the transcripts from several episodes, use entity recognition to categorize people, places, things, etc, and load them into a Neo4j database (via Cypher queries). It turns out there's something called the POLE data model[1] that can be used by law enforcement to help solve crimes. You load all the details into a graph database and evaluate the relationships to aid in solving crimes. I suppose you could argue a criminal investigation is essentially graph traversal.

[1] https://neo4j.com/blog/government/graph-technology-pole-posi...

Edit: typo

271832• 8 days ago

I have had very bad experiences with graph dbs at scale. To the point where I will never again work on a project based on a graph db. YMMV, but I'm done with them forever.

[edit] To elaborate: tuning read and write performance is difficult, essentially everything must be indexed. This results in an explosion in data size--so data that might be X TB in csv format becomes maybe 10X when you consider all the indexes and bloat from the graph db's storage format. Which brings us to the topic of compression: there isn't any. Moreover, graph dbs are basically all quite immature compared to other db software, they haven't seen the test of production to the same degree, nor have they gotten the same attention in terms of bugfixes, performance tuning, etc. So they often have very sharp edges that you encounter under load. So if you like spending tons of money and time on zero value work, choose a graph db!

[another edit] Another problem with graph dbs is they encourage laziness in data modelling. I would echo others' recommendations here: just start with SQL. If it gets to the point where you actually need a graph query language--and you've already appropriately considered your life choices and determined that there's some value to what you're doing--only then should you consider trying to implement something on a graph query engine. But I'm not aware of one that is actually good. That's the problem. If you're at the point where you absolutely need a graph database you are probably at the point where you need to build your own. And you'll probably fail like all the other ones.

hobofan3• 8 days ago

Most graph databases only offer an advantage in query language, as it allows for more ergonomic graph traversal compared to e.g. recursive CTEs in SQL. However with SQL/PGQ, the same query ergonomics are coming to traditional databases.

If you look under the hood there is usually nothing special about graph databases that will make them more performant. If you lay out a query plan side-by side between e.g. Postgres and Neo4J, they will look identical, just that the leaf-nodes in Postgres will be a table-scan, while in Neo4J they will be either a vertex-scan or a edge-scan (which can both be seen as special cases of a table-scan).

As someone that has worked a lot with graph databases in the past, I'd largely recommend not using them. The price you pay in terms of worse ecosystem and less battle-tested maintenance tooling is not worth it to just have better syntax.

StrauXX• 8 days ago

Apache AGE seems like a good way to have the battle testedness of Postgres with a more fluent query language. I have only used AGE in smaller projects so far however.

andriy_koval• 8 days ago

However with SQL/PGQ, the same query ergonomics are coming to traditional databases.

I like how PG19 with PGQ will kill lots of companies and startups.

adsharma4• 8 days ago

Recent benchmarking: https://theconsensus.dev/p/2026/05/29/ladybug-duckdb-and-pos...

Response: https://blog.ladybugdb.com/post/better-graph-database-ball/

lenkite• 7 days ago

Yes, now that Postgres offers property graphs: https://www.postgresql.org/docs/19/ddl-property-graphs.html, which allows ergonomic queries using graph pattern matching syntax, instead of joins, these dbs feel like dodos.

pphysch2• 8 days ago

Graph query languages like Cypher are great, but I am wholly unconvinced by the concept of a dedicated, general-purpose "graph database".

IMO, you're better off just using Postgres/etc, modeling your graph data there, and pulling in subsets of your graph for in-memory analysis. This is for the 99% of enterprises that aren't doing online streaming graph analysis on TB-scale graphs, and the other 1% should probably figure out something tailored* to their specific business model.

* Graph algorithms are more accessible than ever with GenAI code, and efficiently modeling a graph in memory is trivial (it's just structs with pointers to other edges/nodes, plus its nice to have full control over the memory layout).

reaanb2• 8 days ago

We had general-purpose graph databases before graph databases became a thing. I'm talking about relational databases. Values are the vertices, tuples are the edges, FK constraints are inclusion dependencies. In fact, n-ary relations means a hypergraph database, not just a binary graph db.

adsharma4• 8 days ago

Just use postgres (or another SQL db) ignores the following innovations:

* Columnar storage * Compressed Sparse Row on disk * Factorized joins * ASP joins, WCO Joins

Details: https://vldb.org/cidrdb/2023/kuzu-graph-database-management-...

rob743• 9 days ago

I wasn't surprised that it's written in a JVM language, but I was surprised that that language is Java, not JetBrains' very own Kotlin...

atraac• 9 days ago

Youtrack was made long before Kotlin so I suspect the rewrite just wasn't worth it

rob743• 9 days ago

TIL - YouTrack was first released in 2009, Kotlin in 2011, so I wouldn't call it long before, but definitely before. Guess I'm more interested in programming languages than in task management tools, that's probably why I have been aware of Kotlin longer than of YouTrack...

Cthulhu_• 9 days ago

Thing is, iirc Kotlin is mostly compatiable / interchangeable with Java so they could write any new code in Kotlin.

mike_hearn2• 9 days ago

You can port files from Java to Kotlin by pressing a button, but Jetbrains has generally not done bulk ports. They leave it up to individual devs to convert a file when it's being worked on, if the diff and VCS history pollution is worth it.

znpy2• 9 days ago

Object databases routinely go away and routinely come back.

Ten years ago I worked with a database called Versant OODBMS (from Actian). I was a junior sysadmin so i was essentially administering it at a very surface level but skimming the documentation (and trying some of the samples) it was very cool that you could pick essentially any random class, implement an interface (and hence a few method) and that was it, you had a database-serializable object.

The main issue was really scaling out (as in, multiple machines) but otherwise was a really great database.

pjmlp2• 9 days ago

Yes, POET for C++, for example.

http://www.kevra.org/TheBestOfNext/ThirdPartyProducts/ThirdP...

kjs3• 9 days ago

That's funny, one of my buddies from college was one of the OG Versant employees (I assume there's not another OODBMS named Versant). That was in the late 80s.

znpy2• 8 days ago

Cool! I used Versant at work between 2016 and 2019!

rickette• 9 days ago

This is the successor of https://github.com/JetBrains/xodus, but with quite some differences.

l337h4x0rz• 9 days ago

I played around with something similar before called typedb. It also does object oriented graph model which was a bit weird at first after using sql for a long time, but once it clicks there's a lot of thing that you could express surprisingly nicely

marcodena• 9 days ago

is it distributed? It would be awesome to use it with graph neural network due to the O(1) graph traversal

dzonga• 9 days ago

There's also falkorDb (based on redis) to consider

[0] https://github.com/falkordb/falkordb

vanyaland• 9 days ago

Worth clicking into .claude/agents/ in this repo. There are 25 agent definitions, 10 of them code-review dimensions.

iterateoften• 9 days ago

When you see 25 agent definitions, how do you know they are good? How do you know it’s better than 10 or 5 or 1? Is a project with 100 agent definitions better?

RadiozRadioz• 8 days ago

What is interesting about them?

gjvc3• 9 days ago

summary

* AFAICT, this is not (yet) in active use in production YouTrack, which is still using https://github.com/JetBrains/xodus

* the technical leader of the YouTrackDB project, Andrii Lomakin, was one of the main contributors to OrientDB -- see https://medium.com/@youtrackdb

* YouTrackDB is a fork of OrientDB

* this project makes heavy use of Claude Code

* YouTrackDB does not use Kotlin

* this can be used as a network service (rather than just embedded in a single runtime process like in current production YouTrack), but I've not yet got the docker images working to try.

from the blurb

YouTrackDB is a general-purpose object-oriented graph database developed by JetBrains, used internally in production. It implements the Apache TinkerPop API with Gremlin query language support and features O(1) link traversal, schema-less/mixed/full modes, and encryption at rest. The project is a fork of OrientDB, re-architected under the com.jetbrains.youtrackdb package namespace.

jollyllama• 8 days ago

I hope this doesn't complicate the process of deploying YouTrack on-prem. That's the best part about YouTrack; historically, you can deploy on prem with no backing DB. From the outside perspective, it just stores everything to flat files.

YouTrackDB is a general-use object-oriented graph database

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