Database Test Casesor

Why We Chose Neo4j? KUBID SYSTEMS & POWERNIGHT GMBH

AboutKUBID Systems & Powernight GmbH KUBID Systems & Powernight GmbH was founded 2007 in

cooperation with BMVIT (Austrian Federal Ministry for Transport, Innovation and Technology)

Specialist in electronic loyalty and voucher systems Market leader in Austria and Germany in this area Around 2.400 customer companies currently using our system Around 15.000 transactions per day

Databases Databases used in our test cases:

Amazon Aurora Amazon Dynamo Cassandra 2.2.0 MySQL 5.6.26 Neo4j 2.2.5 PostgreSQL 9.4.4

Test Goals Evaluation of different databases regarding speed and time for

importing, deleting and querying data which is organized in a logical tree structure.

In our application we need to access multiple levels of child and parent nodes to calculate properties of each node (multiple times)

Test Setup We used Amazon EC2 instances “t2.small” with 2 GB Memory and 30 GB storage for Cassandra, MySQL,

Neo4j and PostgreSQL We used Amazon EC2 instances “r3.large” with 15 GB Memory and 30 GB storage for Amazon Aurora We used 2000 Read and Write Capacity Units for Amazon DynamoDB We used Debian Jessie as operating system Test data was imported from .csv files For delete and query statements we used language specific commands (SQL, Cypher, ..) Indexes on unique values that exist in a particular column/properties (e.g. id, parent) We used primary and secondary index if database allowed Running cmd line-scripts, tools:

Amazon Aurora - AWS Command Line Interface (AWS CLI) Amazon Dynamo - AWS Command Line Interface(AWS CLI) Cassandra – Command Line Tool (cqlsh) MySQL – Command Line Tool (mysql) Neo4j - Neo4j Shell (neo4j-shell) PostgreSQL - Command Line Tool (psql)

Import and Delete15.000 Rows

DB Import Deleted Amazon Aurora 1.800 seconds 0.523 seconds

Amazon Dynamo 94.602 seconds 89.490 secondsCassandra 1.657 seconds 0.385 seconds

MySQL 4.349 seconds 16.313 secondsNeo4j 0.503 seconds 0.453 seconds

PostgreSQL 0.080 seconds 0.0435 seconds

Import and Delete50.000 Rows

DB Import Deleted Amazon Aurora 2.989 seconds 0.651 seconds

Amazon Dynamo 2200.160 seconds 2394.020 secondsCassandra 2.907 seconds 1.031 seconds

MySQL 9.466 seconds 16.917 secondsNeo4j 1.838 seconds 1.797 seconds

PostgreSQL 0.275 seconds 0.094 seconds

Import and Delete100.000 Rows

DB Import Deleted Amazon Aurora 5.979 seconds 0.903 seconds

Amazon Dynamo 3699.483 seconds 3839.117 secondsCassandra 5.939 seconds 1.056 seconds

MySQL 23.771 seconds 23.922 secondsNeo4j 2.566 seconds 3.259 seconds

PostgreSQL 0.448 seconds 0.128 seconds

Import and Delete250.000 Rows

DB Import Deleted Amazon Aurora 13.549 seconds 1.858 seconds

Amazon Dynamo 9699.511 seconds 9739.145 secondsCassandra 12.073 seconds 1.375 seconds

MySQL 50.957 seconds 29.884 secondsNeo4j 4.288 seconds 3.805 seconds

PostgreSQL 1.279 seconds 0.337 seconds

Import and Delete500.000 Rows

DB Import Deleted Amazon Aurora 25.098 seconds 3.917 seconds

Amazon Dynamo 19399.022 seconds 19538.656 secondsCassandra 21.957 seconds 1.771 seconds

MySQL 55.808 seconds 34.199 secondsNeo4j 8.670 seconds 7.611seconds

PostgreSQL 2.422 seconds 0.993 seconds

Import and Delete1.000.000 Rows

DB Import Deleted Amazon Aurora 45.897 seconds 8.837 seconds

Amazon Dynamo 6583.352 seconds 6019.043 secondsCassandra 43.950 seconds. 2.022 seconds

MySQL 70.583 seconds 46.203 secondsNeo4j 10.102 seconds 9.222 seconds

PostgreSQL 4.703 seconds 2.077 seconds

Import and Delete2.000.000 Rows

DB Import Deleted Amazon Aurora Not tested because previous

performance was too low and expensive

Not tested because previous performance was too low

and expensiveAmazon Dynamo Not tested because previous

performance was too low and expensive

Not tested because previous performance was too low

and expensiveCassandra 96.659 seconds 2.714 seconds

MySQL 84.566 seconds 87.496 secondsNeo4j 21.663 seconds 20.445 seconds

PostgreSQL 5.773 seconds 3.978 seconds

Import and Delete5.000.000 Rows

DB Import Deleted Amazon Aurora Not tested because previous

performance was too low and expensive

Not tested because previous performance was too low

and expensiveAmazon Dynamo Not tested because previous

performance was too low and expensive

Not tested because previous performance was too low

and expensiveCassandra 194.936 seconds 3.813 seconds

MySQL 241.954 seconds 145.150 secondsNeo4j 52.659 seconds 44.891 seconds

PostgreSQL 23.764 seconds 17.328 seconds

Import and Delete10.000.000 Rows

DB Import Deleted Amazon Aurora Not tested because previous

performance was too low and expensive

Not tested because previous performance was too low

and expensiveAmazon Dynamo Not tested because previous

performance was too low and expensive

Not tested because previous performance was too low

and expensiveCassandra 314.084 seconds 4.443 seconds

MySQL 716.830 seconds 537.686 secondsNeo4j 76.982 seconds 61.783 seconds

PostgreSQL 62.924 seconds 50.706 seconds

Query 15.000 Rows Finding root node(s) and counting their immediate children

DB Query timeCassandra 0.155 seconds

MySQL 11.034 secondsNeo4j 0.013 seconds

PostgreSQL 0.054 seconds

Query 50.000 Rows Finding root node(s) and counting their immediate children

DB Query timeCassandra 0.490 seconds

MySQL 11.118 secondsNeo4j 0.022 seconds

PostgreSQL 0.056 seconds

Query 100.000 Rows Finding root node(s) and counting their immediate children

DB Query timeCassandra 0.755 seconds

MySQL 11.191 secondsNeo4j 0.034 seconds

PostgreSQL 0.057 seconds

Query 250.000 Rows Finding root node(s) and counting their immediate children

DB Query timeCassandra 0.778 seconds

MySQL 11.219 secondsNeo4j 0.040 seconds

PostgreSQL 0.058 seconds

Query 500.000 Rows Finding root node(s) and counting their immediate children

DB Query timeCassandra  0.916 seconds

MySQL 11.323 secondsNeo4j 0.043 seconds

PostgreSQL 0.058 seconds

Query 1.000.000 Rows Finding root node(s) and counting their immediate children

DB Query timeCassandra  0.936 seconds

MySQL 11.354 secondsNeo4j 0.044 seconds

PostgreSQL 0.058 seconds

Query 2.000.000 Rows Finding root node(s) and counting their immediate children

DB Query timeCassandra 1.287 seconds

MySQL 11.674 secondsNeo4j 0.050 seconds

PostgreSQL 0.059 seconds

Query 5.000.000 Rows Finding root node(s) and counting their immediate children

DB Query timeCassandra 2.575 seconds

MySQL 11.738 secondsNeo4j 0.055 seconds

PostgreSQL 0.061 seconds

Query 10.000.000 Rows Finding root node(s) and counting their immediate children

DB Query timeCassandra 3.151 seconds

MySQL 11.806 secondsNeo4j 0.059 seconds

PostgreSQL 0.076 seconds

Size of Neo4j Database after Import  

Nodes created Properties set

Relationships created

Relationship types

Database disk usage

15.000 119.992 14.956 1 3 MB50.000 399.992 49.841 1 10 MB

100.000 799.992 99.687 1 19 MB250.000 1.999.992 249.215 1 60 MB500.000 3.999.992 498.380 1 119 MB

1.000.000 7.999.992 996.747 1 450 MB2.000.000 15.999.992 1.993.494 1 895 MB5.000.000 39.999.992 4.983.735 1 2212 MB10.000.000 79.999.992 9.967.470 1 4457 MB

ConclusionWhy Neo4j

Scalable architecture optimized for speed ACID compliance to ensure predictability of relationship-based

queries Supported programming languages (Java, JavaScript, PHP …) Master-slave replication Foreign keys Fast Query Fast Import

Thank you