Neo4j-Databridge is a fully-featured ETL tool specifically built for Neo4j, and designed for usability, expressive power and high performance. It has been created to help solve the most common problems faced by large enterprises when importing data into Neo4j - data locality, multiple data sources and formats, performance when loading very large data sets, bespoke data conversions, inclusion of non-tabular data, filtering, merging and de-duplication... In this webinar, we’ll take a quick tour of the main features of Neo4j-Databridge and understand how it can to help to solve these problems and facilitate importing your data easily and quickly into Neo4j.

1. GraphAware®
Neo4j-Databridge
Enterprise-scale ETL for Neo4j from GraphAware
graphaware.com
@graph_aware

2. Vince Bickers
Principal Consultant @GraphAware
Primary author of Neo4j OGM library
Ingesting data quickly and easily into Neo4j is an obsession :-)
vince@graphaware.com
About me
GraphAware®

3. Importing data - common challenges
Options?
Databridge core features
Demo!
Agenda
GraphAware®

4. Integrating multiple datasources
Filtering, data conversion, non-tabular data…
Update strategies / de-duplication
Bulk load and incremental updates (offline / online)
Performance with large data sets
Ease of use and configuration
Common challenges
GraphAware®

5. Cypher LOAD CSV
Neo4j Batch Importer
Neo4j JDBC ETL / APOC
Talend
Apache Camel
DIY
Neo4j-Databridge
Options?
GraphAware®

6. For
Extremely flexible
Against
CSV files only
Not suitable for large datasets
Need to know Cypher
Relatively slow
Difficult to manage complex imports
LOAD CSV
GraphAware®

7. For
Extremely fast
Can handle very large data sets
Against
Requires data to be pre-processed first
Inflexible
No “memory”
Neo4 Batch Importer
GraphAware®

8. For
Fast: JDBC ETL uses the batch importer under the hood
JDBC mapping files are configurable
Against
JDBC datasources only
Using APOC library requires you to write Cypher
No “memory”
Neo4j JDBC ETL / APOC
GraphAware®

9. For
Pretty interface
Part of a full ETL platform
Against
Cypher queries over REST API
LOAD CSV is much better!
No “memory”
Talend
GraphAware®

10. For
???
Against
It’s not available
Planning to use Spring Data Neo4j ?
Apache Camel
GraphAware®

11. For
Total control!
Against
Time consuming
Hard work
DIY
GraphAware®

12. Data resources and mappings defined using JSON
Command-line shell
Out-of-the-box adapters for common data formats
Direct auto-import from JDBC databases
Full-featured expression language for filtering and more
Wide range of data converters
Supports full and incremental imports
Bulk Load endpoint (offline) and Streaming endpoint (online)
User-extensible with Groovy scripts and the Adapter API
Databridge core features
GraphAware®

13. satellites - Tabular data: (bulk load CSV)
charities - Tabular data (streaming Excel)
olympics - Structured data: JSON
empdb - Auto-import from a MySql database
iomtt - TomTom Itinerary (ITN)
navaid - UK Aviation waypoints (GPX)
hawkeye - 9.4m nodes, 5m edges in 1 minute
Live demo
GraphAware®

14. More info
GraphAware®
WIKI
https://bitbucket.org/vbickers/neo4j-databridge/wiki/Home/
Email
databridge@graphaware.com
Questions
Ask on StackOverflow, using the tags neo4j databridge