Graph database TPC-H benchmark

What is it?

I want to find out the performance of the most popular graph databases as of 2021. I am using TPC-H datasets to conduct the benchmark.

Graph databases

Based on DB-Engines (https://db-engines.com/en/ranking/graph+dbms) ranking of GDBMS, here are the "pure" graph model DB I will test.

• Neo4j
• JanusGraph
• TigerGraph
• Dgraph

Dependencies

• Install TPC-H tools (http://www.tpc.org/tpch/) and generate the data
• Convert the tbl files into csv and json so that the DB are able to import them

How to start

After you config the make file, dbgen executable file will be generated. Execute dbgen to generate tbl data files. Then convert the tbl files into csv files.

import pandas as pd

# customer.tbl
names = ["C_CUSTKEY", "C_NAME", "C_ADDRESS", "C_NATIONKEY", "C_PHONE", "C_ACCTBAL", "C_MKTSEGMENT", "C_COMMENT"]
a = pd.read_csv("customer.tbl", header=None, index_col=False, names=names, sep="|")
a.info()
a.to_csv("customer.csv", index=False, sep="|")

# lineitem.tbl
names = ["L_ORDERKEY", "L_PARTKEY", "L_SUPPKEY", "L_LINENUMBER", "L_QUANTITY", "L_EXTENDEDPRICE", "L_DISCOUNT", "L_TAX", "L_RETURNFLAG", "L_LINESTATUS", "L_SHIPDATE", "L_COMMITDATE", "L_RECEIPTDATE", "L_SHIPINSTRUCT", "L_SHIPMODE", "L_COMMENT"]
a = pd.read_csv("lineitem.tbl", header=None, index_col=False, names=names, sep="|")
a.info()
a.to_csv("lineitem.csv", index=False, sep="|")

# nation.tbl
names = ["N_NATIONKEY", "N_NAME", "N_REGIONKEY", "N_COMMENT"]
a = pd.read_csv("nation.tbl", header=None, index_col=False, names=names, sep="|")
a.info()
a.to_csv("nation.csv", index=False, sep="|")

# orders.tbl
names = ["O_ORDERKEY", "O_CUSTKEY", "O_ORDERSTATUS", "O_TOTALPRICE", "O_ORDERDATE", "O_ORDERPRIORITY", "O_CLERK", "O_SHIPPRIORITY", "O_COMMENT"]
a = pd.read_csv("orders.tbl", header=None, index_col=False, names=names, sep="|")
a.info()
a.to_csv("orders.csv", index=False, sep="|")

# partsupp.tbl
names = ["PS_PARTKEY", "PS_SUPPKEY", "PS_AVAILQTY", "PS_SUPPLYCOST", "PS_COMMENT"]
a = pd.read_csv("partsupp.tbl", header=None, index_col=False, names=names, sep="|")
a.info()
a.to_csv("partsupp.csv", index=False, sep="|")

# part.tbl
names = ["P_PARTKEY", "P_NAME", "P_MFGR", "P_BRAND", "P_TYPE", "P_SIZE", "P_CONTAINER", "P_RETAILPRICE", "P_COMMENT"]
a = pd.read_csv("part.tbl", header=None, index_col=False, names=names, sep="|")
a.info()
a.to_csv("part.csv", index=False, sep="|")

# region.tbl
names = ["R_REGIONKEY", "R_NAME", "R_COMMENT"]
a = pd.read_csv("region.tbl", header=None, index_col=False, names=names, sep="|")
a.info()
a.to_csv("region.csv", index=False, sep="|")

# supplier.tbl
names = ["S_SUPPKEY", "S_NAME", "S_ADDRESS", "S_NATIONKEY", "S_PHONE", "S_ACCTBAL", "S_COMMENT"]
a = pd.read_csv("supplier.tbl", header=None, index_col=False, names=names, sep="|")
a.info()
a.to_csv("supplier.csv", index=False, sep="|")

License