ldbc_snb_interactive_v1_impls VS benchgraph

At first, the plan was to use only the LDBC dataset and write different queries for the dataset, but LDBC has a set of well-designed queries that were specifically prepared to stress the database. Each query targets a special scenario, also called “chock point.” Not to be mistaken, they do not have deep graph traversal doing around 100 hops, but they are definitely more complex than the ones written for the Pokec dataset. There are two sets of queries for the LDBC SNB: interactive and business intelligence. LDBC provides a reference Cypher implementation for both of these queries for Neo4j. We took those queries, tweaked the data types, and made the queries work on Memgraph. Again, to be perfectly clear, this is NOT an official implementation of an LDBC Benchmark; this goes for both interactive and business intelligence queries. The queries were used as the basis for running the benchmark.

During the run of a typical benchmark, you can run specific queries for a fixed period of time or take a chunk of queries, execute them, and measure elapsed time. Either way, you need a decent amount of queries (same query with different arguments), and for that, you need a bigger dataset. On top of that, testing performance on the more extensive scaled datasets is necessary. To put things into perspective for query requirements, on some of the queries that are being run, the database executes up to 300k queries or less, depending on the query complexity. For a detailed look into statistics, take a look at the benchmark.json file that holds all the results from the benchmarks. There you can see how many specific queries were executed per particular test.