Kenelyze’s January 2023 Release: Visualizing Data from Graph Databases

Kenelyze can now seamlessly connect with various leading graph databases and import and visualize data on the fly!

As opposed to traditional databases, graph databases store data as nodes and the relationships between them. This is a perfect fit for storing connected data (or, data shaped as a network), as it allows very quick lookups of network structures and enables flexible modeling of datasets as a set of interconnected entities from the outset.

Next to Kenelyze’s proven ability to generate all kinds of network visualizations from table-based datasets, it is now also possible to directly connect to Memgraph, Neo4j, AnzoGraph and ONgDB database instances and visualize any data of interest. The focus here is on allowing both non-technical and technical users to work with the data in the graph database: visualizations can be made based on searches and node expansions, while it is also possible to input custom Cypher queries and visualize more advanced data structures.

Here’s a quick overview of what Kenelyze can do from this release onwards:

🔎 Search all node labels and properties in graph databases and visualize search results on the fly
➕ Expand and collapse nodes and their neighbors to quickly populate subgraphs of interest
💬 Ingest users’ custom Cypher queries and visualize the resulting nodes and relationships directly
✏️ Edit the nodes, relationships and properties in the database directly from Kenelyze’s interface
📊 Calculate graph and node-level metrics (e.g. community detection, node centrality measures) for any subgraph returned from the database
📍 Quickly generate network schemas to view the exact structure of the data model in the database
📁 Export any network created in Kenelyze (including those from local files) to Cypher queries to quickly populate graph databases with new data

You can find more details on what the implementation of these features in Kenelyze looks like in the user interface below.

Graph Database Data Import

The Import Data screen now allows users to choose between importing data from a local file or from a graph database:

When importing data from a database, there are a few fields which need to be completed in order to be able to connect, including the type of database (Memgraph, Neo4j, AnzoGraph or ONgDB), the preferred protocol (bolt://, neo4j://, or their secure versions), the database’s host address, plus a username and password (if required). When connecting to a Neo4j instance, it is also possible to input a specific database name to connect to.

After filling out these details, Kenelyze provides a number of ways to start working with the data in the graph database:

The first option allows connecting to the database and visualizing data based on searches (more on the search functionality below). The second option allows direct input of custom Cypher queries to visualize any resulting nodes and relationships directly. The final option imports a random selection of nodes and links, and is handy if you want to get a quick view on what the data in the database looks like.

Expanding and Collapsing Nodes

Any node added from a graph database can be expanded (adding the nodes connected to it) and collapsed (removing the nodes connected to it) at will from the node’s context menu:

It is possible to expand/collapse all neighbors at once, or focus on nodes with specific labels by picking the labels of interest from the corresponding menu item. If a node is expandable (which means it has more neighbors than those currently visible), its label is italic.

Database Options

When visualizing data from a graph database, Kenelyze shows a new icon in the left menu bar which includes various options:

From here, it is possible to input further custom Cypher queries and add data to the visualization directly. The ‘View Network Schema’ button allows users to view the data model used in the database – it generates an overview of all node labels and relationship types and visualizes these in a separate window:

The ‘Clear Network’ button removes all data from the current visualization.

It’s also possible to set various options related to how Kenelyze visualizes the nodes and relationships in the database. When “Keep connected nodes” is selected, any nodes which are still connected to other nodes after a node collapse are not removed from the visualization. Enabling “Add neighboring nodes” makes sure Kenelyze also immediately visualizes the neighboring nodes of any search results added to the visual. “Add missing links” ensures that any links of newly added nodes to existing nodes are also added when expanding a node.

Searching Database Data

Kenelyze can search the contents of any textual node property of interest available in the graph database, and return the search results as nodes in visualizations. The node property to search can be picked from the Search Options panel. It is also possible to switch between database searches and searches in the currently visible network. The latter allows quick look-ups of already added nodes in the current visualization.

Database searches are case insensitive and return results which contain the search query in the value of the selected node property. When viewing search results, it is possible to add all search results to the network at once, or pick individual results of interest:

Editing Database Data

When “Apply network edits” is enabled, it is possible to directly edit data in the database from within Kenelyze. Any edits made to the network in Kenelyze are applied to the source data in the graph database as well (assuming the user has the right permissions). Edits include addition, removal or merging of nodes or links, as well as addition, removal and changes to node or link attributes.

For example, when adding a node to the visualization in Kenelyze’s Edit Mode, a window pops up to set the node’s label and properties:

Adding the node then adds it to the current visualization as well as to the source data in the database. The same holds for relationships, as well as for any changes made to attributes from the Table View.

Exporting networks to Cypher

Any network created in Kenelyze can now be exported to a Cypher file which contains all necessary query statements to import the nodes and links into a graph database of choice. This can be very valuable when quickly wanting to populate a graph database with data based on Excel or CSV files – Kenelyze can create the network structure (nodes, relationships and any properties) on the fly during its import process, after which it can be imported directly into the database using the exported Cypher statements.

Do you work with one of the above graph databases and are you looking for new ways to visualize your data? Or are you interested in how your existing data can be visualized as a graph/network? I’d be happy to chat and show you how Kenelyze can help you out.

If you require any support with regard to these new features, please don’t hesitate to reach out to


Do you have general questions or need support? Mail us at

Kenelyze is a product by Kenedict Innovation Analytics