hop VS tarindexer

If you're looking for a visual and more intuitive way to load data to Neo4j, you might want to have a look at Apache Hop. Hop comes with tons of functionality to load data to Neo4j.

Apache Hop is a great open source orchestration platform with excellent native Neo4j support.

Have you checked out Apache Hop? https://hop.apache.org/ It is a very powerful no-code open source ETL tool.

Apache Hop https://hop.apache.org/

You could look into Apache Hop. Open source with Salesforce connectors. Powerful free option for reverse ETL. https://hop.apache.org/

I would get familiar with an ETL tool. Apache Hop is excellent, opensource, and has native support for neo4j. It will make your imports easier to see the "flow" - also easier to share/collaborate with others. It also gives you support to use several methods (direct from RDBMS, from CSV, or running code like your python example) all from within the same workflows/pipelines, so you can use the best method/tool for a particular part of your process.

I used Apache HOP as an ETL to integrate the ERP data from RangerMSP into a Neo4j knowledgegraph. Then connected the ERP data to our other vendors data using their web APIs (Office365/sharepoint/teams), backups, infrastructure monitoring/alerting to create other workflows that performed automations and validations of our service delivery. The reporting is so so much easier, faster, and more contextual since relationships are created as the data is built/modified, rather then when queried as in an RDBMS.

I'm a pentaho pdi user that wants to give a try to Apache Hop. I've started the gui and learned a bit how to import from pdi, create a new workflow/pipeline, made some test. Now I've to move on but reading the docs at https://hop.apache.org/ I can't find informations I need:

You can try Apache Hop

The bioinformatics community uses block based gzip compression (bgzip) [0]. The gzip standard allows for blocks so, using an additional index file, you can use it to seek to arbitrary locations and uncompress the block.

gzip compression is maybe not optimal now and the block segmentation reduces the efficiency even further.

Though not very standard, there is also a tar indexer program [1] that allows you to create an index on tar files to do the same.

My information is at least a couple years old so things may have changed.

[0] http://www.htslib.org/doc/bgzip.html

[1] https://github.com/devsnd/tarindexer

The pieces are there. https://github.com/devsnd/tarindexer/blob/master/tarindexer.py is a prototype of indexing and seeking a tar file in python. https://github.com/pauldmccarthy/indexed_gzip allows indexing and seeking a gzip file. If those pieces of code were combined it could give you efficient targeted file extraction, but you'd need to find a coder with enough time and motivation to fuss with it.

There exists a utility called tarindexer [0] that can be used for random access to tar files. An index text file is created (one time) that is used to record the position of the files in the tar archive. Random reads are done by loading the index file and then seeking to the location of the file in question.

For random access to gzip'd files, bgzip [1] can be used. bgzip also uses an index file (one time creation) that is used to record key points for random access.

[0] https://github.com/devsnd/tarindexer

[1] http://www.htslib.org/doc/bgzip.html