We’re making it easier to bring your data into Neo4j AuraDB! The Import Service now supports direct connections to Snowflake alongside existing CSV and relational database imports. BigQuery and Databricks support will be coming next.

A new AI-powered schema analysis helps infer primary and foreign keys—even when they’re not explicitly defined—automating graph model generation. This means faster, more seamless imports from your enterprise data ecosystem.

Get started today in the Aura Console under Import Service. Read more in the blog post.

We’re pleased to announce the availability of our first new data source in the Console Preview. If you’re not already familiar with the Console Preview, head over to https://console-preview.neo4j.io.

With this release, you’ll see a new way of accessing import options under Data Services > Import. You’ll now find a new, more comprehensive set of data sources, the first becoming available being PostgreSQL, with more to follow soon. The existing CSV import option remains available.

Note: Your source database will need to be accessible over a public IP address to configure the data source.

Once successfully connected, you’ll be guided through steps to create a graph model and mapping ready for import. Whenever possible, constraints in your source database will be used to create a configuration automatically.

The graph models and mapping are saved for reuse under the Graph Models tab.

In contrast to the CSV import flow which streams files from your client machine, the import jobs for new data sources now run in Aura infrastructure. You can see the status of Import jobs in the corresponding tab and long-running import jobs continue running after you log out of the console.

Once you’re ready to see the results of your load, head over to Explore or Query to start interacting with your new graph.

If you have any feedback, head over to https://feedback.neo4j.com/data-importer to share your thoughts.

The latest release of Data Importer brings support for node property indexes. For properties you refer to frequently, indexes can speed up your queries dramatically. It's now possible to configure indexes directly in data importer. You'll find the UI to configure indexes in the details panel:

Read the docs to learn more!

This release of Data Importer brings a number of small changes that make using Data Importer that little bit easier :

The Import preview is now the last part of Workspace to migrate from the old visualisation to the new one used in Explore and Query. As well as being more visually consistent, it's now more responsive and easier to navigate.

We'll be exploring upping the limits on the number of preview nodes, do leave us feedback if you think that'd be useful.

That's all for now. We're working on some big new capabilities in import, more on that to follow in the coming months 😀. As always keep your feedback coming on feedback.neo4j.com.

This release of Data Importer brings two new features:

We've made a slight tweak to the Preview feature, allowing you to optionally preview selected parts of your our graph. If you have a particularly complex model, it can sometimes be hard to see how all the different nodes and relationship types being previewed are linking. In these scenarios you can use "Preview selected" to only preview selected parts of the model. This can help you validate specific parts of the model are mapped as expected. In the example below, only the Product, Supplier and SUPPLIES parts of the model will be previewed when using the "Preview selected" option.

The Data Importer UI gives you a convenient way to generate your graph model and map data, but what happens if you want to take the import logic and use it somewhere else without the UI? Or what if the Data Importer UI doesn't quite allow the complex transformations that you need?

For these scenarios, we are now providing you the option to view and download a Cypher script representing your model and mapping. You can use these as-is, or adapt for more complex needs.

Examples of where you might use this generated code include:

The load script itself is commented to help you understand the purpose of the different parts and where you might need to make changes, depending on where you're running it.

You can also choose to download the files with your script, which will give you a handy zip of the script and your files.

We hope you enjoy using these new features and as always please head over to https://feedback.neo4j.com/data-importer with any feedback.

In this release of Data Importer, we're pleased to announce changes to make the UI clearer, as well as allowing you to use Data Importer as a simple standalone graph modelling tool. Here's a quick run-down of those changes:

The Files panel now hides automatically when you don't have enough space to easily view your model and mapping. You can always bring it back temporarily to overlay on you graph model when screen space is limited. You can also tuck it away permanently when it's not needed.

The Mapping panel has undergone a number of changes:

There are quite a few other small changes made in the UI, we hope you agree they make the UI cleaner and established users don't find them too disorientating. As always, please do head over to leave us your feedback on https://feedback.neo4j.com/data-importer. Thanks!

You'll now see that the run button changes to a stop button that also reports progress. You can use this button to terminate the load in the event you need to make tweaks before relaunching the load.

You'll also notice that the preview button has changed to a preview icon.

Previously Data Importer created properties for empty strings, occupying unnecessary storage. From this release properties will no longer be set for empty strings, resulting in smaller database sizes.

You'll also notice that incomplete mappings are no longer rendered as dashed lines. Instead you'll now see a green check mark against nodes and relationships that are fully mapped.

This release of Data Importer introduces a new way to load more data sources without the need for pre-processing. By allowing you to apply simple filters to files we're enabling loads in more scenarios, including:

We're going to take a quick look at how file filtering can help you with the latter example.

Consider the following subset of the Northwind data model showing Orders, the Products they contain and the Shippers they are shipped by.

In the classic Northwind dataset, these are represented by different tables like , , and . When extracting data from more graph-like sources however, it is not uncommon to be provided with wide node lists and relationships lists that contain all the nodes and all the relationships in just two files.

Here's what an example exported from our very own Neo4j Bloom looks like (but could equally apply to any other graph-like export):

bloom-relationships-export.csv

In the nodes file you'll notice the node types are identified by the column and relationship types in the relationships file by the column.

Prior to the file filtering feature, you needed to separate the nodes files into three files representing the three node types and the relationships file into two files representing the two relationship types.

With file filtering, now optionally available under the File dropdown in the Mapping Panel, you can apply include filters to keep rows only relevant to the Nodes or Relationships in your model. Here's an example of applying the file filter to the file to ensure it only keeps the rows where the column has values.

You'll notice the filter when applied, gives you feedback as you type on how many matches were found. For performance reasons only the first 10,000 rows of any file are scanned, so even if you don't see matched in this feedback, there may still be matches further down your file.

The same filtering principle applies for the nodes file, in this example mapping to the Product node and only keeping the rows in the file where values in the column equal .

For now file filtering supports exact string matches, but we'd love to hear your feedback on the utility of the filtering functionality and other things you'd like to see. As always, please head over to https://feedback.neo4j.com/data-importer to leave us your feedback.

That's all for now, thank you for reading!

This release of Data Importer brings a couple of small UI updates to make common tasks easier and clearer.

The files panel is now collapsible, giving you more space to work on the graph model when needed.

We've observed that it isn't always clear to new users what the different parts of the From/To relationship mapping UI represent, so we've reworked it to hopefully make it a little clearer.

We now explicitly call out which nodes and ID properties are at the and ends of a relationship, and which file columns we are expecting you to match them up with to create valid relationships.

We continue to automatically populate these for you when your relationships use the same file for nodes at each end (and you've already selected their IDs). The main time you need to populate these fields manually is when you're using a separate file to define relationships between nodes.

As always, keep your feedback coming on https://feedback.neo4j.com/data-importer.

You'll see a number of small updates land today that make Data Importer easier to use:

Keep your feedback coming on feedback.neo4j.com/data-importer.