Q: Can neo4r handle large graph datasets efficiently?

It may struggle with performance on large datasets due to HTTP-only connections, which are slower than Bolt. The package is better suited for moderate-sized graphs in analytical workflows, as bulk operations like load_csv() are available but might be limited by network latency.

Q: How do I visualize Neo4J data in R using neo4r?

Query with call_neo4j(type = 'graph'), then use unnest_graph() to flatten results and convert to igraph or visNetwork objects. The README provides examples with ggraph for plotting and visNetwork for interactive visualizations.

Q: What's the difference between neo4r and RNeo4j?

neo4r is newer, focusing on tidyverse integration and modern R practices with tibble outputs, while RNeo4j is an older package with a different API. neo4r offers better compatibility with packages like dplyr and purrr, but RNeo4j might be more stable for legacy projects.

Q: How to import CSV data into Neo4J with neo4r?

Use the load_csv() function with an on_load query to specify how data maps to Neo4J nodes and relationships. The README shows an example with the northwind dataset, sending CSV from a URL and executing Cypher on load.

Q: Does neo4r support transactions or ACID compliance?

The README doesn't highlight transaction management; it focuses on query execution and data retrieval. For ACID compliance, you'd rely on Neo4J's inherent properties, but neo4r's HTTP interface may not fully expose advanced transactional features compared to Bolt drivers.

Question 1

How do I connect neo4r to a remote Neo4J server?

Accepted Answer

Use the neo4j_api$new() function with the URL, user, and password parameters. For example, con <- neo4j_api$new(url = 'http://localhost:7474', user = 'neo4j', password = 'plop'). Note that only HTTP/HTTPS is supported, not Bolt.

Question 2

Can neo4r handle large graph datasets efficiently?

Accepted Answer

It may struggle with performance on large datasets due to HTTP-only connections, which are slower than Bolt. The package is better suited for moderate-sized graphs in analytical workflows, as bulk operations like load_csv() are available but might be limited by network latency.

Question 3

How do I visualize Neo4J data in R using neo4r?

Accepted Answer

Query with call_neo4j(type = 'graph'), then use unnest_graph() to flatten results and convert to igraph or visNetwork objects. The README provides examples with ggraph for plotting and visNetwork for interactive visualizations.

Question 4

What's the difference between neo4r and RNeo4j?

Accepted Answer

neo4r is newer, focusing on tidyverse integration and modern R practices with tibble outputs, while RNeo4j is an older package with a different API. neo4r offers better compatibility with packages like dplyr and purrr, but RNeo4j might be more stable for legacy projects.

Question 5

How to import CSV data into Neo4J with neo4r?

Accepted Answer

Use the load_csv() function with an on_load query to specify how data maps to Neo4J nodes and relationships. The README shows an example with the northwind dataset, sending CSV from a URL and executing Cypher on load.

Question 6

Does neo4r support transactions or ACID compliance?

Accepted Answer

The README doesn't highlight transaction management; it focuses on query execution and data retrieval. For ACID compliance, you'd rely on Neo4J's inherent properties, but neo4r's HTTP interface may not fully expose advanced transactional features compared to Bolt drivers.

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