GraphSummit Stockholm - Neo4j - Knowledge Graphs and Product Updates

Neo4j Inc. All rights reserved 2024
Neo4j Product Vision
and Roadmap
David Pond
Lead Product Manager

SAFE HARBOR ROADMAP
DISCLAIMER
The information presented here is Neo4j, Inc. confidential and does not
constitute, and should not be construed as, a promise or commitment by
Neo4j to develop, market or deliver any particular product, feature or
function.
Neo4j reserves the right to change its product plans or roadmap at any
time, without obligation to notify any person of such changes.
The timing and content of Neo4j’s future product releases could differ
materially from the expectations discussed herein.
2

Neo4j
Product capabilities launched in 2023/2024
5
● Parallel Runtime - faster analytical Queries
● Change Data Capture - better data integration
● Autonomous clustering & Fabric - limitless
scalability
● Graph Schema & constraints
● Backup with point-in-time recovery
● Incremental import
● Neo4j/AuraDB Ops Manager for managing
databases
● Aura Enterprise Database on all clouds
(AWS, GCP, Azure)
● SOC II Type 2 compliance, AuraDB APIs, RBAC
configuration
● Private Link & CMEK
● Log forwarding & performance metrics - better
observability
● Workspace - unified developer experience
● GraphQL Support & Simplified Drivers API
● Bloom support for GDS algorithms
● GDS Python API
● Knowledge Graph Embeddings
● Longest Path & Topological Sort Algorithm
● Vector Search & index
● Embedding APIs & LLM Models - Real Time
integration
● OpenAI + MS Azure OpenAI, VertexAI, AWS
Bedrock, Langchain, LlamaIndex etc. - Real Time
GenAI integration

6
Cloud Scale
• Procure through Aura Console or via
Cloud Marketplace
• Zero maintenance, automated
upgrades and highly available
• Scalable and elastic, on-demand
• Enterprise-grade security
• SOC II Type 2 compliance
• Easier RBAC configuration with Aura
Console
• Private link
• CMEK
• Observability with Ops Manager,
performance metrics and logs
forwarding

Customer Managed Keys (Encryption)
7 Neo4j Inc. All rights reserved 2024
What is it
Aura encrypts all data at transit &
rest by default.
Customer Managed Keys (CMK)
is an alternative way to protect
cloud data for security conscious
Enterprises, enabling customers
to manage their own keys for
encryption / decryption at disk on
Aura using Key Management
Services (KMS) from their Cloud
Service Provider.
Why it is important
Customers can protect their own
data, control access and have
the ability to revoke access, even
from Neo4j.
Customers can adhere to their
own stringent security policy
around access and key rotation,
on top of Aura’s Enterprise grade
default security and compliance
posture.

Customer Managed Keys (Encryption)
8

Neo4j
Ops Manager
9

Unified Product Experience
Aura Console
Graph Tools
Ops
Management

Improvements in Bloom / Explore
Data Slicer
GDS Algos

12
April 12, 2024
Welcome GQL!
GQL - Graph Query Language
The first new ISO language since 1987
GQL-fueled additions in Cypher:
• Node and relationship expressions WHERE
clause
• Richer label expressions
• Sophisticated pattern repetitions
• SQL-like synonims
• GQL Error codes
• GQL is Here: Your Cypher Queries in a GQL World
• GQL: The ISO Standard for Graphs Has Arrived
• ISO GQL: A Defining Moment in the History of
Database Innovation

13
Graph Pattern
Matching
Improved expressivity of
graph navigation with
Quantified Path Patterns,
a more powerful and
performant syntax to
navigate and traverse
your graph.

NEO4J 5.0 NEW CAPABILITIES
Database Enhancements
Graph Pattern Matching Example → Fraud Rings
14
QPP
MATCH path=(a:Account)-[:PERFORMS]->(first_tx)
((tx_i)-[:BENEFITS_TO]->(a_i)-[:PERFORMS]->(tx_j)
WHERE tx_i.date < tx_j.date
AND 0.80 <= tx_i.amount / tx_j.amount <= 1.00
){3,6}
(last_tx)-[:BENEFITS_TO]->(a)
WHERE size(apoc.coll.toSet([a]+a_i)) = size([a]+a_i)
RETURN path
accountNumber:2
amount: 1000
date: 2023-01-01T10:10:10.000+0000
accountNumber: 1
amount: 900
date: 2023-01-02T10:10:10.000+0000
amount: 729
date: 2023-01-04T10:10:10.000+0000
accountNumber: 4
accountNumber: 3

15
New constraints on nodes,
relationships and properties:
● Node/Relationship unique
property
● Node/Relationship property
existence and type
● Node/Relationship keys
NEO4J 5 NEW CAPABILITIES
Graph Schema

Graph Schema / Graph Type
16
The definition of the informational content of a schema
(or rather a graph type), comprising:
● A set of node type descriptors
(also known as a node type set).
● A set of edge type descriptors
(also known as an edge type set).
● A node type name dictionary that maps node type
names,
which are identifiers, to node types contained in the node
type set of this graph type descriptor such that each
node type name is mapped to a single node type.
● An edge type name dictionary that maps edge
type names,
which are identifiers, to edge types contained in the
edge type set of this graph type descriptor such that
each edge type name is mapped to a single edge type.
CREATE OR REPLACE GRAPH TYPE FraudDet
(a:AccountHolder { FirstName :: STRING!,
LastName :: STRING!,
UniqueId :: STRING! }
...) REQUIRE UniqueId IS KEY,
(c:CreditCard {AccountNumber :: STRING!,
Balance :: FLOAT!,
...} ...) REQUIRE AccountNumber IS KEY, ...
(a)-[:HAS_CARD ...]->(c),
(a)-[:HAS_ACCOUNT ...]->(b),...
CREATE OR REPLACE DATABASE foo
...
[WITH GRAPH TYPE FrautDet]
...

17
Parallel Runtime
Speed up
analytical
queries up to
100x

18
Parallel Runtime
Speed up
analytical
queries up to
100x

19
Parallel Runtime
Speed up
analytical
queries up to
100x MORE CORES

20
Parallel Runtime
Speed up
analytical
queries up to
100x
FASTER
QUERIES
MORE CORES

21
BLOCK FORMAT
Memory Optimized
and Future Proof
An implementation of graph-native
that’s informed by more than a decade
of experience supporting real-world
production graph workloads.
Neo4j is still graph-first; block format
is:
• Native graph storage
• Optimized for connected data
• Index-free adjacency
Block format supersedes all previous
store formats.
Migrate, convert, import into Block
Format

CHANGE DATA CAPTURE
Automated Real-Time Change Tracking

Graph Data at Scale
Autonomous Clustering
Easy, automated horizontal scale-
out
Composite Databases
Federated queries and sharded graphs

Graph Data at Scale

Properties Sharding
Users’ Connections TOPOLOGY DATABASE
SHARDED PROPERTY
DATABASES
Parallel
data load
Rolling
updates on
demand

AI Enabler
Graph Data Science & Generative AI
26

© 2023 Neo4j, Inc. All rights reserved. 27
Knowledge
Graphs
and GenAI
How can you use domain-
specific knowledge to
rapidly build accurate,
contextual, and
explainable GenAI
applications?

28
Knowledge Graphs + LLMs
28
Facts
Explicit
Explainable
Words
Implicit
Opaque
KGs LLMs
+
Left Brain + Right Brain

Retrieval Augmented Generation (GraphRAG)
Vector + Graph Search
29
● avoid hallucinations
● ignore LLM training data
● only use language skills
● fetch relevant information from
reliable (enterprise) datasources
● often uses vector and/or full-text
search for starting points
● use context from knowledge graph

Graph + Vector = Semantic Search
30
Find similar documents.
Find related information.
Combine for more
accurate results within a
relevant context.
Vector Index
Graph Structure
Knowledge Graph
Similarity Search
Pattern Matching

31
What is a Knowledge Graph?
An information architecture with layered connections.
Or a digital twin of reality or your organization.
DATA INFORMATION KNOWLEDGE INSIGHT MEANING
records sets relationships patterns layers

RAG with Neo4j
32
Find similar documents,
content and data
Expanded context for related
information and ranking
results
Improve GenAI inferences and
insights. Discover new
relationships and entities
Unified search, knowledge graph and data science capabilities to
improve RAG quality and effectiveness
Vector Search,
Full-text Search,
Geospatial, Pattern
match
Data Science
Knowledge Graph

33
Knowledge Graph Complementary Benefits
33
LLM
Human
Application
Knowledge
Graph
Extend LLM
knowledge
through RAG
Invite human
exploration &
curation
Advanced
application
features & analysis

34
1 Knowledge Graph Construction
Gen AI use cases LLM
Knowledge
Graph
neo4j.com/labs/genai-ecosystem/llm-graph-builder

35
Knowledge Graph
Construction with
Cypher Templates

36
Knowledge Graph Construction
neo4j.com/labs/genai-ecosystem/llm-graph-builder

Human
37
Knowledge
Graph
2 RAG-based Chat Applications
neo4j.com/labs/genai-ecosystem/rag-demo/

38
Natural Language
Search combining
explicit and implicit
relationships

39
RAG-based Chat Applications
neo4j.com/labs/genai-ecosystem/rag-demo/

Application Human
40
Knowledge
Graph
2 RAG-based Chat Applications
3 RAG-enhanced General Applications

41
Natural Language
assistants and co-
pilots,
rooted in business
policy
Prompt +
Relevant
Information
Embedding API LLM API
User
Database
Search
Prompt Response
Relevant Results
Knowledge
Graph
Application

● Integrate Neo4j with leading LLM open-
source frameworks such as LangChain,
LlamaIndex & More
● Call LLM APIs natively via Cypher using
product integration or open-source APOC
(extended) library
● Agnostic LLM orchestration connecting
graphs to OpenAI, AWS Bedrock, GCP
Vertex AI, Azure, Anthropic, Hugging
Face, and other proprietary and open
source foundation models
Integrate with the GenAI Ecosystem
42
GenAI Stack
Application
Generative AI & Embedding Models
Orchestration
Grounding Knowledge Graph
Neo4jGraph
Neo4jVector
GraphCypherQAChai
n
Neo4jGraphStore
Neo4jVectorStore
KnowledgeGraphIndex
Neo4j GenAI Integrations
Text | Chat | Embedding
NL Query | Image Gen
Neo4j Drivers
Java
Python JavaScript
neo4j.com/labs/genai-ecosystem

POWERING GENERATIVE AI APPS
Neo4j’s GenAI Roadmap
● Co-Pilots & integrations in Neo4j Browser, Bloom,
Data Importer, NeoDash, Docs
● Cloud Integrations: GCP Vertex AI, AWS Bedrock,
Azure OpenAI
● Scalable and integrated Vector Search, additional
Graph Embeddings
● GraphRAG eval framework
● More framework integrations: Langchain,
LlamaIndex, SemanticKernel, Spring.AI, Haystack
43
Coming 2024+

● Parallel Runtime for faster analytical Queries
● Block Format for efficient and future proof graph
storage
● Change Data Capture (CDC) better data integration
● Autonomous clustering and Composite Database for
limitless scalability
● Graph Schema, Improved Backup recovery,
incremental import
● Neo4j Ops Manager for managing databases
● Aura Database on all clouds (AWS, GCP, Azure)
● SOC II Type 2 & HIPAA compliance, AuraDB APIs,
RBAC configuration
● Better observability with security log forwarding
Performance metrics forwarding (EAP)
● Private Link & CMEK
Neo4j product capabilities launched in 2023/24
44
● Unified Developer Experience with Neo4j Workspace
● Quantified Graph Pattern Matching
● Call in Transactions
● Self-service Data Import (more coming soon)
● GraphQL Support
● Simplified Drivers API
● Bloom support for Graph Data Science algorithms
● Graph Data Science Client
● Knowledge Graph Embeddings
● Vector Index, similarity search & vector similarity
● Real Time integration with Embedding APIs & LLM
Models
● GenAI Integrations (OpenAI + MS Azure OpenAI,
VertexAI, AWS Bedrock, Langchain(Python & JS),
LlamaIndex, Haystack, Spring AI, LangChain4j)

45
Follow us!
@neo4j
Enjoy
GraphSummit
Stockholm
david.pond@neo4j.com

GraphSummit Stockholm - Neo4j - Knowledge Graphs and Product Updates

Recommended

Recommended

More Related Content

Similar to GraphSummit Stockholm - Neo4j - Knowledge Graphs and Product Updates

Similar to GraphSummit Stockholm - Neo4j - Knowledge Graphs and Product Updates (20)

More from Neo4j

More from Neo4j (20)

Recently uploaded

Recently uploaded (20)

GraphSummit Stockholm - Neo4j - Knowledge Graphs and Product Updates