Understanding Neo4j AI Graph Databases: Review and Alternatives

Mayanka Pant
Jan 30, 2024

Graph analytics is being used by enterprises more and more to extract insights from large, complex data collections. Leading graph database Neo4j gives data scientists and developers powerful tools for creating intelligent processes and apps. 

This tutorial attempts to assist newcomers to Neo4j with basic and useful ideas. It offers a code sample and glossary of important words for installing and configuring Neo4j. It is advised to have some prior understanding of graph theory and database systems. 

What Is a Neo4j or Graph Database?

Neo4j is a highly scalable graph database management system designed specifically for computing connection transversal and storage. For semantic searchers, it alternatives nodes and connections in a graph structure for tables or documents. 

Important Points

  • Node-based data: Users, corporations, and other data entities are stored as nodes in Neo4j. 
  • Relationship Clarity: Data relationships are made readily apparent by the representation of connections by edges.
  • Flexibility: Data is saved without a pre-established model, which makes analysis flexible. 
  • Relationship Variety: While edges have a type, direction, and start and finish nodes, nodes may have several connections.
  • Typical Use Cases: Businesses use Neo4j to get exact insights from intricate searches involving users and customer data

Why Neo4j or Graph Database?

In the quickly changing digital world of today, businesses struggle with enormous amounts of data. Finding patterns and concluding data are crucial. Businesses require database technology that maximizes data relationships by treating relationship details as the main entity in order to handle this. 

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Relational databases now in use are capable of managing these linkages, but their ability to handle data relationships is still lacking. Many business demands may be satisfied by using graph databases. They use a more effective, adaptable style to record relationships with nodes, or data components. They are excellent at quickly traversing data, which makes them perfect for changing the needs of the organization. 

Comparing Graph and Relational Databases

The following difference table can clarify the answer to the question "How does a relational database differ from a graph-based database?" if you are still having trouble understanding it.

Relational Database

Graph Database


It has tables with rows and columns.

It has nodes and edges showing relationships among each other.


Relationships are connected across tables where they are established using foreign keys between tables.

Considering data, the relationships are represented between edges and nodes.

Complex Queries

Relational databases require complex joins between tables.

Graph databases operate quickly and do not require joins.

Top Use-Cases

Relationational databases are widely adopted for transaction applications such as online transactions and accountings.

Graph databases are mainly used for relationship-heavy use cases, including fraud detection and recommendations engines.


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Benefits of Neo4j

Graph databases, as we all know, are the way to go quickly in mission-critical businesses. There are several advantages to utilizing Neo4j, however. We’re going to examine it right now:

  • Its data model is straightforward, adaptable, and strong. It is easily customizable to meet your application’s and your company’s requirements.
  • It uses real-time data to offer outcomes.
  • For large enterprise real-time systems using transactional contracts, it provides high availability.
  • Neo4j is a schema-free database that offers linked and semi-structured data in an easy-to-understand format. 
  • Neo4j allows you to represent and browse (traverse/navigate) linked data more quickly than with conventional databases.
  • Neo4j uses ASCII-art syntax to feed a declarative query language (Cypher Query Language) to graphically represent the graph. This language has easily comprehensible instructions that are understandable by humans. 
  • Neo4j is quick because it makes it easy to obtain and browse through larger amounts of linked data.
  • Complex joins are not necessary when using Neo4j to get related or linked data. Without joins or indexes, retrieving its relationship properties or nearby nodes is simple.
  • Higher vertical scalability, enhanced operating characteristics, more concurrency, and easier tweaking are all offered by Neo4j.

Features of Neo4j

In short, we have seen what Neo4j is up to this point. Why is Neo4j such a hit? The benefits of Neo4j as a popular graph database utilized by all types of corporations and enterprises, as well as the differences between Neo4j and relational database management systems. 

This section will look at several important Neo4j features:

Data Model Featuring Adaptable Schema

The property graph model is the data model that Neo4j uses. The graph is made up of nodes that stand in for different entities. Relationships link these nodes. Data is stored in key-value pairs, or properties, by both nodes and relationships. Neo4j doesn’t enforce a set schema, thus you may add or delete attributes to suit your needs. Neo4j also offers schema restrictions for improved data management.

ACID Characteristics

Rich ACID characteristics are supported by Neo4j:

A: Atomic nature

C: Consistency

I: Isolation

D: Durability

Dependability & Scalability

Neo4j enables you to grow the database without compromising data integrity or query processing time by scaling the volume and number of read/write operations. Additionally, it provides replication authorization for data security and dependability.

Integrated Web Apps

Additionally, Neo4j provides an integrated Neo4j browser web application that you may use to create and access your graph data. 

GraphDB & Indexing

Neo4j uses the Property Graph Data Model and Apache Lucence to maintain indexes. 

Several Other Broad Characteristics

  • To deal with programming languages like Java, Spring, Scala, etc., it offers REST API.
  • In addition to using native graph storage and native GPE (Graph Processing Engine), it supports UNIQUE restrictions.
  • It offers Java Script for use with Node JS and other UI MVC frameworks.
  • Neo4j supports two kinds of Java API: Native Java API and Cypher API. These APIs allow you to create reliable Java apps.
  • To interact with other databases like MongoDB or Cassandra, Neo4j also allows query data exporting to JSON and XLS formats.

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Neo4j Property Graph Data Model 

Neo4j stores and processes its data using a property graph data model, as seen in the features section. The following are some of the essential components and aspects of the property graph data model that will be covered in this section:


Initially, one must understand that nodes, which are discrete objects or data items, are the building blocks of a graph data structure and are represented by relationships. 

Nodes are represented by circles and may have one or more labels to categorize their nodes.


A connection between a source node and a destination node is represented by a relationship. Only bidirectional and unidirectional (i.e., always having a direction) options are available. You may only indicate it using arrow keys. 

To categorize their connections, relationships need to be classified as either "Start Node" "From Node" "To Node" or "End Node."


To provide more information, nodes, and relationships may contain characteristics that are key-value pairs.

How Can I Set Up Ubuntu To Use Neo4j?

The installation and configuration of Neo4j on an Ubuntu 20.04 server will be covered in this part.


It is advised to use the following settings while configuring Neo4j:

15GB of free storage, 1GB of RAM, and a single-core server

Root mode should be used for all commands. Sudo must be used after controls if you are not in root mode. For your convenience, we will be utilizing the sudo command throughout this lesson.

20.04 Ubuntu

Setting up Neo4j

Neo4j is not formally included in the standard package repository of the official Ubuntu package repositories. We will add the package source referring to the Neo4j repository’s address to install the upstream-supported package from Neo4j. The GPG key from Neo4j will then be added for verification. We will then install Neo4j after that. 

Step 1: We begin by making updates to the current package list.


Step 2: Install packages 

To secure the installation, a few required programs for HTTPS connections will be installed in this phase. It’s possible that your systems already have this program installed by default. Nevertheless, you may safely execute the following command. 


Step 3: Include a GPG Security Key

In this step, we will add the GPG security key for the official Neo4j package repository. By using this key, you can be sure that the installation you are doing is coming from the official Neo4j upstream repository. 




Step 4: Include the Neo4j Repository in the List of Packages Managed by Your System.


Step 5: Install the Neo4j Package 

Installing the Neo4j package and all of its dependencies completes this module. It should be noted that in order for Neo4j to function, this installation will additionally download and install a suitable Java package. To approve the program installation, type “Y”. The installer will skip this step if Java is already installed on your computer. 


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Start the Neo4j Service.

Step 1: Activate Neo4j.Service

Following installation, Neo4jought to be operational. To have it start upon a system reboot, we must activate it as a “neo4j.service” service. 


Step 2: Use the systemctl Command

Next, use the “systemctl” command to check the status of Neo4j. Making sure everything is operating as planned requires taking this crucial step. 


Utilization and Testing with Neo4j

You are now ready to test the database connection and set up the admin user on your machine after installing Neo4j and its dependencies and starting its services.

Step 1: Communicate with Neo4J

The internal utility will be launched using the “cypher shell” command so that we may interact with the Neo4j database from the command line.



You will first need to provide a username, which is set to ‘Neo4j,’ along with a password. Following a successful authentication attempt, you’ll be asked to change the administrator password to something more personal.

After updating the password, you will be able to access the interactive “Neo4j” prompt. This is where you may insert and query in the Neo4j database. 

Step 2: Make Use of the Exit Command

After creating an administrator password and attempting to connect to Neo4j, use the exit command. 



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Clauses, Functions, Datatypes, and Operators in Neo4j CQL

Neo4j supports the Cypher Query Language (CQL) as its query language, as we covered in the previous section. We will now examine a few of the CQL available operators, data types, clauses, and functions. 

Neo4j CQL Clauses




Searches data with a specified pattern.


Functions like MATCH but allows null for missing parts.


Adds conditions to CQL queries.


Locates initial points through legacy indexes.


Imports data from a locally stored CSV file.


Creates nodes, properties, and relationships in the DB.


Updates labels on nodes and properties on nodes/relationships


Checks if a pattern exists; creates if not.


Removes nodes, relationships, and paths from the DB.


Eliminates elements and properties from nodes/relationships.


Updates data within a list.


Matches and creates a unique pattern.


Specifies the query result set.


Arranges query output in order (used with RETURN or WITH).


Restricts result rows to a specific value.


Chains query parts together.


Expands a list into rows.


Joins outcomes of multiple queries.


Invokes a deployed procedure in the database.

Neo4j CQL Functions




Used when working with string literals.


Conducts aggregation operations on CQL query results.


Used to fetch details of relationships, such as start and end nodes.

CQL Data Types for Neo4j

The majority of Neo4j data types resemble those of the Java programming language. They are also used in defining a node's or a relationship's attributes.

Data Type



Defines boolean values (True, False).


Describes an 8-bit integer.


Determines 16-bit integers.


Defines 32-bit integers.


Describes 64-bit integer.


Describes a 32-bit floating-point number.


Expresses a 64-bit floating-point number.


Represents a 16-bit character.


Represents a literal string.

CQL Operators for Neo4j

The operators that Neo4j CQL supports are as follows:

Operator Type


Mathematical Operators

+, -, *, /, %, ^

Comparison Operators

>, <, >=, <=, =

Boolean Operators


String Operators


List Operators

+, IN, [X], [X?..Y]

Regular Expression


Matching String


Neo4j Alternatives

Whether a developer is starting a basic web application or a huge project, choosing the right database is an important choice. The performance and course of a project may be greatly affected by the database. This post will introduce you to several Neo4j substitute databases, highlighting the capabilities and applications that best fit your requirements at the moment. 


Memgraph distinguishes itself as an open-source, high-performance graph database that can replace Neo4j without adding to its complexity or expense. It is a fantastic alternative that is made especially for real-time analytics and graph processing. Organizations needing real-time graph analytic skills will find Zmemgraph Lab, an intuitive graph visualization tool, to be the perfect option due to its extensive features, which include high-performance graph algorithms, support for complicated graph queries, and more. 


A NoSQL multi-model database system that is open-source and supports graph, document, and key-value data models is called ArangoDB. It can manage and query intricate connections both within and across databases. 


Dgraph is a distributed native graph database that is open-source and designed for organizing and searching massively linked data. Because it is designed to manage intricate connections in data, it is appropriate for applications that need effective graph traversals. 


With its combination of a graph database, reasoning engine, and data virtualization features, Stadog is an enterprise-grade Knowledge Graph platform. It gives businesses the ability to store, query, and model intricately linked data, which serves as a basis for creating intelligent applications. 


Fauna is a cloud-based application programming interface (API) for distributed document-relational databases intended for contemporary use cases. It may be used for a variety of purposes since it offers an adaptable, multi-model database with ACID transactions.


The main goal of the Neo4j graph database launch was to assist customers in resolving a wide range of technical and commercial challenges. Whether you rely on graph transactions, market research, operational improvements, or anything else, it is easy to use and meets your use cases. The process of integrating new tools with the remainder of your current system has always been smooth. 

Frequently Asked Questions

What is the purpose of Neo4j?

Neo4j is perfect for applications containing complicated interactions, such as knowledge graphs, social networks, and recommendation engines, as it can be used to manage and query graph data.

Is Neo4j NoSQL or SQL?

A NoSQL database called Neo4j was created especially for graph data, not SQL.

What drawbacks does Neo4j have?

Neo4j has drawbacks like as a learning curve, resource-intensive operations on big graphs, and restricted support for certain query types.

Is Neo4j still applicable?

Graph databases are still in use across a variety of sectors, therefore Neo4j is still relevant for applications needing sophisticated relationship modeling and queries.

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