Follow up on the latest improvements and updates.

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July 3, 2026

new

AuraDB Virtual Dedicated Cloud

AuraDB Professional

AuraDB Free

AuraDS Professional

AuraDS Enterprise

AuraDB Business Critical

New Aura User Management APIs

Neo4j is thrilled to introduce the new Aura User Management REST APIs, bringing comprehensive programmatic control to user lifecycle management across both Organization and Project levels!  Previously driven primarily through the Aura Console UI, this new programmatic capability eliminates operational friction for enterprise teams looking to scale efficiently.  We've built this feature specifically to support automated deployments and modern DevOps workflows,
These new APIs allow you to seamlessly integrate Neo4j Aura into your existing Identity and Access Management (IAM) workflows, CI/CD pipelines, and Internal Developer Platforms (IDPs). This unlocks "Zero-Touch" user onboarding, where automated API calls handle provisioning and align with Aura's unified organization-level identity model. 
Refer to the Aura API Specification documentation  for information on using each endpoint and the Aura API Overview documentation for how to access the Aura API.
The Organization-level endpoints, admins can programmatically manage invitations (GET, POST, DELETE /organizations/{org_id}/invites) and oversee the entire user directory: including fetching metadata, adjusting global organization roles, or offboarding users entirely (GET, PATCH, DELETE /organizations/{org_id}/users). 
To support granular access control, Project-level endpoints empower development teams to manage memberships natively within their specific project workloads. You can programmatically list project users, grant access, update project roles, or revoke specific project memberships (GET, POST, PATCH, DELETE /organizations/{org_id}/projects/{project_id}/users). 
This dual-layer framework ensures that project-level access can be granted instantly or cleanly terminated during onboarding and offboarding workflows, eradicating manual entry errors and significantly elevating your security posture. 

July 3, 2026

new

AuraDB Virtual Dedicated Cloud

AuraDB Professional

AuraDB Free

Data Importer

Import

New Console

Import Service: Support for List and Vector Datatypes

We are pleased to announce that the Import Service now supports List and Vector datatypes. Whether you are bringing in graph embeddings for GenAI applications or working with list attributes, you can now easily map and import these complex datatypes into Neo4j.
This support is fully integrated across both local file workflows and remote data sources. Here is what you can expect:
1. Local CSV Flow
For your local CSV workflow you can manage your formatting configurations directly within the files panel. Simply click the ...
 menu next to your Data source and select Set delimiters
.
This opens a dedicated configuration modal where you can define the exact characters separating your array and vector values.
2. CSV Files in Cloud Buckets
When importing CSV files hosted in cloud storage buckets, you can configure array and vector delimiters during your data source setup flow. Providing these delimiters triggers the automatic detection of list and vector types, ensuring your cloud-hosted file properties are parsed automatically.
3. Strongly-Typed Data Sources
 (Parquet, RDBMS, & Cloud Data Warehouses)
If you are connecting to remote data sources that natively support structured or typed data—such as Apache Parquet files, relational databases, or cloud data warehouses—the Data Importer does the heavy lifting for you. Compatible source types are automatically recognized and offered as options mappable directly to their equivalent Neo4j types (such as vector<float32>
, string[]
, or float[]
).
Once selected, you can easily fine-tune your configuration (such as specifying vector dimensions) right inside the property settings UI.
We Want to Hear From You!
We are continuously evolving the data loading experience. Please try out the new list and vector support and share your thoughts, feature requests, or bug reports with us at feedback.neo4j.com/data-importer.

June 30, 2026

new

AuraDB Virtual Dedicated Cloud

AuraDB Professional

AuraDB Free

AuraDS Professional

AuraDS Enterprise

AuraDB Business Critical

Neo4j Aura June Database Release

The Neo4j Aura June release has started to roll out, commencing on AuraDB Free and progressing to higher tiers later.

Cypher 25 Features

CALL { ... } IN CONCURRENT TRANSACTIONS
now supports
DISJOINT BY
, a deadlock prevention mechanism that eliminates lock contention in parallel write workloads natively. High concurrency ingestion, particularly when merging nodes with unique constraints or creating relationships, has always been vulnerable to deadlock, as parallel threads compete for the same locks simultaneously.
DISJOINT BY
resolves contention at scheduling time, before any transaction is attempted. See the Cypher Manual → Batch scheduling and deadlock prevention with DISJOINT BY.
GRAPH TYPE
moves from public preview to GA in this release. You can now define, enforce, and validate your graph schema at the database level in production workloads with the stability guarantees that come with a fully supported feature. See the Cypher Manual → Graph types.
Extend
SHOW CURRENT GRAPH TYPE
to be able to return lists of virtual nodes and relationships representing the graph type (similar in format to the output of db.schema.visualization()) instead of the current string representation. To get the graph version of the command, use
SHOW CURRENT GRAPH TYPE AS GRAPH
. See the Cypher Manual → SHOW CURRENT GRAPH TYPE AS GRAPH.
For customers using Change Data Capture (CDC), we have added a
txCommitTime
column to the
db.cdc.current()
procedure. This update allows clients to conveniently identify the commit time of their most recent transaction alongside the transaction identifier.
Vector
SEARCH
queries now support
IN
for filtering, allowing queries like:

MATCH (movie:Movie)
  SEARCH movie IN (
    VECTOR INDEX moviePlots
    FOR $queryVector
    WHERE movie.genre IN ["Horror", "SciFi"]
    LIMIT $topK
  )
RETURN movie.title AS title, movie.rating AS rating

See the Cypher Manual → Predicates for vector search with filters.

Other relevant updates

Preview feature

: an improved vector search that uses our new Hi-Fidelity Quantized Vector Search method. HFQ performs an initial expanded search on the quantized vectors, then re-ranks the results using the full precision vectors. This should make queries faster, reduce memory requirements, and increase recall accuracy when compared to the previous default quantized vector index. HFQ adds the following options to

CREATE VECTOR INDEX

, vector.quantization.type and vector.default_search_expansion_factor.

To try the preview of HFQ:

CREATE VECTOR INDEX moviePlots IF NOT EXISTS
FOR (m:Movie)
ON m.embedding
OPTIONS { indexConfig: {
  `vector.quantization.type`: 'binary',
  `vector.default_search_expansion_factor`: 2.0,
  `vector.dimensions`: 1536,
  `vector.similarity_function`: 'cosine'
}}

HFQ requires an index re-build and is expected to be GA in the next release.

Aura Graph Analytics (AGA)

Native projections are now available in AGA via both Cypher and the GDS Python client.
Project-level Machine Learning model publishing is now supported, automatically granting model access to all members of a project.

Security

Upgraded netty to version
4.2.15.Final
in order to resolve several CVEs.

Bug fixes

Fixed a bug that allowed cached pages to exceed the configured limit.
Fixed a bug where outbound network chunks for secondaries were not flushed properly. This could lead to a buffer overflow in the outbound.
Fixed a bug in the pipelined runtime where an
OR EXISTS
subquery containing ordering could silently drop a result row:

MATCH (c:Customer)
WHERE c.vipStatus = true OR EXISTS { MATCH (c)-[:PLACED]->(o:Order) RETURN o ORDER BY o.total DESC }
RETURN c.name

Fixed a record format bug where undirected scans of multiple relationship types omitted sibling relationships, resulting in a ~50% undercount in the output.
Fixed an issue that let a User Defined Function (UDF) be defined as part of a Property-Based Access Control (PBAC) privilege. This isn't supported and wouldn't have worked as a user might have expected.

For full details of all updates and fixes in this release, as well as links to relevant documentation please visit: Release Notes: Neo4j Aura Database – June 2026.

June 29, 2026

new

AuraDB Professional

AuraDB Free

AuraDS Professional

AuraDS Enterprise

AuraDB Business Critical

Aura Graph Analytics

Neo4j Fleet Manager

Aura Project Deletion now available

We are happy to announce that project deletion is now available within the Aura Console for all self serve users.

Required roles:

Project Administrator, Organization Administrator (with Project Administrator role), Organization Owner

Delete a project

Go to Project settings → Delete Project
Select Delete Project
A warning modal appears.
Type the name of the project to confirm, then select Confirm Deletion.

Recover a deleted project

A project can be restored within the 30 day recovery window that begins when the project is deleted. Aura instances will automatically resume. Compute billing will resume once the resources are active.

Go to Organization settings → Recover deleted projects
Locate the project you wish to recover.
Select Restore Project.

See documentation for details: https://neo4j.com/docs/aura/managing-projects/delete-and-restore-projects/

June 26, 2026

new

improved

AuraDS Professional

Desktop

New Console

AuraDB Business Critical

Neo4j Desktop 2 v2.2.0

Neo4j Desktop 2.2.0 adds deeper Aura integration, branding changes, improves query authoring and graph exploration workflows, and brings a round of usability fixes across Bloom and Dashboards.
What's new
Connect Neo4j Desktop to your Aura account using the Aura API.
Neo4j Desktop can now connect to your Aura account using the Aura API. This makes it easier to discover Aura organizations, projects, and instances directly from Desktop during key workflows like adding remote connections or migrating local databases. The goal is to reduce manual setup, cut down on context switching, and lower the risk of connection errors when moving between local development and Aura environments.
Get started by creating your client credentials in Aura console and then add the downloaded API key file in Desktop settings.
Neo4j Desktop tools branding
We have renamed our Desktop tools suite and the ‘Explore’ tool. 
In the side menu, 'Tools' --> 'Studio', and 'Explore' --> 'Bloom'. All functionality remains the same. 
This change, also applied to Aura console, introduces a clearer 'Studio' experience across our different products
💻 Desktop
 - For individual developers working with local/remote Neo4j databases with clear on-ramps to Neo4j Aura as a cloud environment for production and teams.
☁️ Aura console
 - For teams on Neo4j Aura, or self-managed customers utilizing registered remote connections.
🏢 Enterprise Studio
 - For self-managed, paid enterprise customers who require localized or highly secure deployments, especially air-gapped networks with no external connectivity. Recently launched, read more about Enterprise Studio.
Tool updates
Here are the other main changes in each of the tools in Desktop v2.2.0:
Query
Added schema-based completions. Cypher editor now shows path templates for valid next relationship/labels.
Added keyboard navigation for graph visualisation.
Bloom (previously Explore)
Advanced graph analytics: added the ability to run graph analytics using the GDS plugin or Aura Graph Analytics on a projection based on the entire database.
Improved support for Virtual Graphs.
Fixed numerous smaller issues and improvements.
Dashboards
Added presentation mode.
Added support for moving cards between dashboard pages.
Fixed map chart coordinate handling and resizing issues.

June 9, 2026

new

AuraDB Virtual Dedicated Cloud

AuraDB Professional

AuraDB Business Critical

Aura Graph Analytics

Native Projections now in Aura Graph Analytics

We are excited to announce support for

Native Projections

in Aura Graph Analytics (AGA)! You can now efficiently project graphs directly from your underlying database storage into your GDS session using either standard Cypher commands or the GDS Python client.

What's new?

Previously, loading graphs required query-based approaches that, while flexible, weren't always optimized for sheer volume. With native projections, you can explicitly specify node labels, relationship types, and their associated properties to execute high-performance bulk graph loading.

Why this matters ⚡

Because native projections read directly from the underlying database storage rather than executing complex Cypher filtering, they offer

the absolute best performance and scalability for bulk graph loading

. This is the ideal tool when you need to project entire databases or massive subgraphs into memory quickly, without needing complex topological transformations.

How to use it 🛠️

Native projections are fully integrated into both your standard Cypher workflow and the GDS Python client (v1.22+). You can start using it right away:

Via Cypher:

CALL gds.graph.project(
  'my_native_graph',
  'Person',
  'KNOWS',
  {
    memory: '2GB'
  }
)

Via Python Client:

G, result = gds.v2.graph.project_native(
    graph_name="my_native_graph",
    node_label_filter=["Person"],
    relationship_type_filter=["KNOWS"]
)

For complete details on configuring these projections, supported parameters, and underlying mechanics, please check out the official documentation on Native projections in Aura Graph Analytics.

June 1, 2026

new

AuraDB Virtual Dedicated Cloud

AuraDB Professional

AuraDS Professional

AuraDS Enterprise

AuraDB Business Critical

🚀 New Billing API available

We are excited to announce the general availability of two new Aura API endpoints designed to give you full control over your billing data:

/usage
: Extracts billed usage for a specific period and Aura organization.
/ledger
: Extracts historical credit balances for a specific period and Aura organization.

Automate Your Billing Insights

Say goodbye to manual UI exports. You can now automatically feed your billing data directly into your own data warehouse to:

Track trends over highly customized timeframes.
Isolate costs by identifying the exact projects, services, resources, or providers driving your spend.
Forecast effectively by predicting and acting on credit balance depletion before it impacts your workflows.

Availability

: These endpoints are live today for all paying customers via Aura API v2beta1. Setup instructions can be found in the Aura public documentation.

May 28, 2026

new

AuraDB Virtual Dedicated Cloud

AuraDB Professional

AuraDB Business Critical

Larger 5TB Adjustable storage now available on AWS

AuraDB Business Critical and Virtual Dedicated Cloud customers running on AWS can now configure up to 5TB of storage as standard, directly through the Aura Console or Aura API.

Example from AuraDB VDC Console UI

Eligible customers can now provision higher storage capacities for both new and existing AuraDB Business Critical and Virtual Dedicated Cloud instances on AWS, within supported memory-to-storage ratios, for example:

192GB instances now support up to ~3TB of storage
256GB instances now support up to ~4TB of storage
384GB and 512GB instances now support up to ~5TB of storage

Building on the adjustable storage capabilities previously introduced, this enhancement gives customers:

Even greater flexibility
: scale storage based on workload needs without increasing compute
Improved cost efficiency
: avoid additional compute costs when only more storage is required
A smoother experience
: configure storage directly without manual processes, custom workarounds, or support requests

For more information on this feature, please read our documentation.

May 27, 2026

new

AuraDB Virtual Dedicated Cloud

AuraDB Professional

AuraDB Free

AuraDS Professional

AuraDS Enterprise

AuraDB Business Critical

Neo4j Aura May Database Release

The Neo4j Aura May release is rolling out now, starting with AuraDB Free and progressing to higher-tier instances.

It includes Fleet Manager discovery, expanded Cypher 25 GQL compliance, new native string functions, and runtime fixes.

🚀 New Cypher 25 features (GQL standards)

Composable SHOW commands: Combine multiple Cypher commands in one query and mix them with other Cypher statements. Supported commands include
SHOW INDEXES
,
SHOW CONSTRAINTS
,
SHOW FUNCTIONS
,
SHOW PROCEDURES
,
SHOW DATABASES
, and more.
ACYCLIC
with
SHORTEST
and
ANY
paths: You can now combine
ACYCLIC
with
ANY
,
SHORTEST
,
ALL SHORTEST
, and related path selectors.
New native string functions:
string.indexOf
,
string.join
, and
string.regexReplace
are now native Cypher functions. Related
apoc.text.*
functions are deprecated.

🛠️ Bug fixes

Fixed a network channel concurrency issue that could cause out-of-order messages and slower writes.
Disabled a parallel runtime planner behavior that could increase memory use for some variable-length patterns. Re-enable per query with
CYPHER parallelRepeatHeuristic=enabled
.
Fixed
COUNT(DISTINCT)
overcounting in the pipelined runtime.
Auth rules with invalid time functions now fail at creation time.
Fixed
stDev()
returning 0 instead of null for empty input.

For full details of all updates and fixes in this release, as well as links to relevant documentation please visit: Release Notes: Neo4j Aura Database – May 2026.

May 27, 2026

new

AuraDB Virtual Dedicated Cloud

AuraDB Professional

AuraDS Professional

AuraDS Enterprise

AuraDB Business Critical

🚀 New Aura Billing Experience is now available for all customers with a payment method

What’s new?

Managing your organization’s spend just got a lot easier. Starting today,

Organization Admins

and

Owners

will see two new pages under the

Organization Billing

menu:

Billing Overview
: Your new financial dashboard. Get a month-to-date usage snapshot at a glance, featuring a brand-new burndown chart and credit balance tracking for prepaid accounts.
Cost Explorer
: An interactive tool to slice and dice your historical usage. Customize your view with interactive charts and export your data to CSV for deeper analysis.

How to get the most from the new pages

💳 Billing Overview: Your Daily Snapshot

As your new billing landing page, this view gives you an immediate look at current-month consumption and remaining credit balances - no digging required.

🔍 Cost Explorer: Granular Spend Tracking

Understand exactly what is generating costs and when. The

Cost Explorer

aggregates data across all projects and billing accounts in your organization, empowering you to:

Analyze spending patterns
: Track trends over custom timeframes and bucket data by day or month.
Pinpoint cost drivers
: Identify the exact projects, services, resources, or providers driving up your bill.
Investigate financial impact
: Deep-dive into the your resource consumption cost to optimize your budget.

Check out our documentation for more details.

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