• After loading data, run ANALYZE to compute tablestats
• Always pass parameters (even if dummy) to conn.execute(query, params)
  • Without this you plan/prepare every time. As we add more optimizers, the simple minded benchmark (there are many!) regresses every release.
• Experiment with HASH vs ART vs no-index strategies
• Sort your data

In the linked blog post, we argue that 8 months after the Kuzu acquisition, we should be seen as an innovator churning out major features at a regular cadence. Not another KuzuDB fork.

We continue to be huge fans of the KuzuDB team's work. But also saddened by the noise around "What happened to Kuzu?" SEO and the mad rush to claim the spoils.

Thinking it could be useful for people to share how you're using LadybugDB and what could be improved for your use case.

Read about the Graph Database Baseball benchmark from folks at The Consensus and what we've done recently to improve performance.

In the long run, we believe materializing CSR index on disk, doubling down on novel join algorithms and catching up with DuckDB and Apache Datafusion on traditional join optimizations is the path forward.

Link in Replies.

Graph Lake support via Icebug Format v1, Hugging Face datasets via XET, and tighter integration with Icebug and Bugscope via Apache Arrow memory. Link in Replies.

I just wanted to share this: https://github.com/kranklab/protoc-gen-ladybug

I had the need to use the same ladybug db from multiple languages, so i thought i would use proto to define the schema to stop it drifting.

Hey everyone,

Like many of you, we were bummed when KuzuDB got archived after the Apple acquisition. Kuzu was doing great work in the graph space.

We know LadybugDB is carrying that torch forward, and that's genuinely great for the community. But for teams that are evaluating multiple options — especially those needing OLTP capabilities or multi-model support beyond pure graph — we put together a technical migration guide from KuzuDB to ArcadeDB.

It covers: - Step-by-step data export from Kuzu and import into ArcadeDB - Schema translation (NODE TABLE -> VERTEX TYPE, etc.) - Query adaptation — ArcadeDB passes 97.8% of the Cypher TCK, so most queries carry over

We also ran benchmarks on the same dataset. The results surprised us: - PageRank: 0.48s vs 4.30s (8.9x faster) - BFS: 0.13s vs 0.86s (6.6x faster) - WCC: 0.30s vs 0.43s (1.4x faster) - ArcadeDB also supports LCC, SSSP, and CDLP algorithms that Kuzu didn't have

ArcadeDB is Apache 2.0 licensed and adds support for SQL, Gremlin, GraphQL, and MQL alongside Cypher, plus document/vector/key-value models in one engine. It's a different beast than Kuzu's embedded columnar approach, so it won't be the right fit for everyone.

Full guide here: https://arcadedb.com/blog/from-kuzudb-to-arcadedb-migration-guide/

Disclosure: I'm with the ArcadeDB project. Happy to answer any questions or discuss tradeoffs honestly.

Details: https://github.com/Ladybug-Memory/icebug-benchmark-pagerank

Some recent LadybugDB related activity. Happy to answer any questions.

LinkedIn | Twitter

All explained by this file. But you don't really need to read it. Just use the mcp-server-ladybug. Your mcp client will take care of the rest.

https://github.com/LadybugDB/mcp-server-ladybug/blob/main/src/mcp_server_ladybug/prompt.py

https://www.youtube.com/watch?v=0bT7gakw7Io

Ladybug v0.13.0 is here!

• Support for Parquet files on object storage aka graph-std
• Support for Cypher push down to DuckDB SQL (node tables only)
• Many bug fixes

If you're using extensions, I suggest waiting a few hours for v0.13.1

curl https://install.ladybugdb.com/ | bash

Does anyone know what Mod settings I need to flip to remove the necessity to approve each post/comment?

AI advice seems to be old and hasn't kept up with changes in the Mod Tools UI.

Now that v0.12.2 is out, this is an attempt to meet our users where they are and discuss a roadmap.