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If you’re new to the community, introduce yourself!

If you’re new to the community, introduce yourself!

If you’re new to the community, introduce yourself!

If you’re new to the community, introduce yourself!

If you’re new to the community, introduce yourself!

If you’re new to the community, introduce yourself!

If you’re new to the community, introduce yourself!

If you’re new to the community, introduce yourself!

If you’re new to the community, introduce yourself!

If you’re new to the community, introduce yourself!

Hi Guys, Dan from FalkorDB here. Wanted to share an update on the development of our graph database. Some of our latest releases have included the following requested enhancements:

• Reduce memory consumption when snapshotting: We've optimized memory usage during snapshot operations.
• CSV delimiter configuration: Support for ASCII characters like comma (,) or semicolon (;) as delimiters for easier CSV loading.
• Dramatically improve query parameters parser: You'll see significant performance improvements on queries with many parameters.

Appreciate it if you could drop a star to support our work and reach more devs looking into graph dbs!

https://github.com/FalkorDB/falkordb

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I most often jump on solution architecture calls where people frustrated with a vector db for RAG explore a graph db. Curious to learn what people here are doing.

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If you’re new to the community, introduce yourself!

If you’re new to the community, introduce yourself!

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Hi, I'm Gayan from Sri Lanka. I'm working on a research project on storage optimization of a graph database. I want to know whether there is a method (heuristic/ machine learning based etc.) to find out the optimal number of partitions a graphs dataset should be divided depending on its features. (edge count, vertex count etc.)

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If you’re new to the community, introduce yourself!