litegraph

Lightweight graph database with relational and vector support built using Sqlite, designed to power knowledge and artificial intelligence persistence and retrieval.

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LiteGraph is a property graph database designed for knowledge and artificial intelligence applications. It supports graph relationships, tags, labels, metadata, data, and vectors. LiteGraph can be used in-process with LiteGraphClient or as a standalone RESTful server with LiteGraph.Server. The latest version includes major internal refactor, batch APIs, enumeration APIs, statistics APIs, database caching, vector search enhancements, and bug fixes. LiteGraph allows for simple embedding into applications without user configuration. Users can create tenants, graphs, nodes, edges, and perform operations like finding routes and exporting to GEXF file. It also provides features for working with object labels, tags, data, and vectors, enabling filtering and searching based on various criteria. LiteGraph offers REST API deployment with LiteGraph.Server and Docker support with a Docker image available on Docker Hub.

README:

LiteGraph

LiteGraph is a property graph database with support for graph relationships, tags, labels, metadata, data, and vectors. LiteGraph is intended to be a unified database for providing persistence and retrieval for knowledge and artificial intelligence applications.

LiteGraph can be run in-process (using LiteGraphClient) or as a standalone RESTful server (using LiteGraph.Server).

New in v4.x

Major internal refactor for both the graph repository base and the client class
Separation of responsibilities; graph repository base owns primitives, client class owns validation and cross-cutting
Consistency in interface API names and behaviors
Consistency in passing of query parameters such as skip to implementations and primitives
Consolidation of create, update, and delete actions within a single transaction
Batch APIs for creation and deletion of labels, tags, vectors, edges, and nodes
Enumeration APIs
Statistics APIs
Simple database caching to offload existence validation for tenants, graphs, nodes, and edges
In-memory operation with controlled flushing to disk
Additional vector search parameters including topK, minimum score, maximum distance, and minimum inner product
Dependency updates and bug fixes
Minor Postman fixes
Inclusion of an optional graph-wide HNSW index for graph, node, and edge vectors

Bugs, Feedback, or Enhancement Requests

Please feel free to start an issue or a discussion!

Simple Example, Embedded

Embedding LiteGraph into your application is simple and requires no configuration of users or credentials. Refer to the Test project for a full example.

using LiteGraph;

LiteGraphClient graph = new LiteGraphClient(new SqliteRepository("litegraph.db"));
graph.InitializeRepository();

// Create a tenant
TenantMetadata tenant = graph.CreateTenant(new TenantMetadata { Name = "My tenant" });

// Create a graph
Graph graph = graph.CreateGraph(new Graph { TenantGUID = tenant.GUID, Name = "This is my graph!" });

// Create nodes
Node node1 = graph.CreateNode(new Node { TenantGUID = tenant.GUID, GraphGUID = graph.GUID, Name = "node1" });
Node node2 = graph.CreateNode(new Node { TenantGUID = tenant.GUID, GraphGUID = graph.GUID, Name = "node2" });
Node node3 = graph.CreateNode(new Node { TenantGUID = tenant.GUID, GraphGUID = graph.GUID, Name = "node3" });

// Create edges
Edge edge1 = graph.CreateEdge(new Edge { TenantGUID = tenant.GUID, GraphGUID = graph.GUID, From = node1.GUID, To = node2.GUID, Name = "Node 1 to node 2" });
Edge edge2 = graph.CreateEdge(new Edge { TenantGUID = tenant.GUID, GraphGUID = graph.GUID, From = node2.GUID, To = node3.GUID, Name = "Node 2 to node 3" });

// Find routes
foreach (RouteDetail route in graph.GetRoutes(
  SearchTypeEnum.DepthFirstSearch,
  tenant.GUID,
  graph.GUID,
  node1.GUID,
  node2.GUID))
{
  Console.WriteLine(...);
}

// Export to GEXF file
graph.ExportGraphToGexfFile(tenant.GUID, graph.GUID, "mygraph.gexf");

Simple Example, In-Memory

LiteGraph can be configured to run in-memory, with a specified database filename. If the database exists, it will be fully loaded into memory, and then must later be Flush()ed out to disk when done. If the database does not exist, it will be created.

using LiteGraph;

LiteGraphClient graph = new LiteGraphClient(new SqliteRepository("litegraph.db", true)); // true to run in-memory
graph.InitializeRepository();

// Create a tenant
TenantMetadata tenant = graph.CreateTenant(new TenantMetadata { Name = "My tenant" });

// Create a graph
Graph graph = graph.CreateGraph(new Graph { TenantGUID = tenant.GUID, Name = "This is my graph!" });

// Create nodes
Node node1 = graph.CreateNode(new Node { TenantGUID = tenant.GUID, GraphGUID = graph.GUID, Name = "node1" });
Node node2 = graph.CreateNode(new Node { TenantGUID = tenant.GUID, GraphGUID = graph.GUID, Name = "node2" });
Node node3 = graph.CreateNode(new Node { TenantGUID = tenant.GUID, GraphGUID = graph.GUID, Name = "node3" });

// Create edges
Edge edge1 = graph.CreateEdge(new Edge { TenantGUID = tenant.GUID, GraphGUID = graph.GUID, From = node1.GUID, To = node2.GUID, Name = "Node 1 to node 2" });
Edge edge2 = graph.CreateEdge(new Edge { TenantGUID = tenant.GUID, GraphGUID = graph.GUID, From = node2.GUID, To = node3.GUID, Name = "Node 2 to node 3" });

// Flush to disk
graph.Flush();

Working with Object Labels, Tags, and Data

The Labels property is a List<string> allowing you to attach labels to any Graph, Node, or Edge, i.e. [ "mylabel" ].

The Tags property is a NameValueCollection allowing you to attach key-value pairs to any Graph, Node, or Edge, i.e. { "foo": "bar" }.

The Data property is an object and can be attached to any Graph, Node, or Edge. Data supports any object serializable to JSON. This value is retrieved when reading or searching objects, and filters can be created to retrieve only objects that have matches based on elements in the object stored in Data. Refer to ExpressionTree for information on how to craft expressions.

The Vectors property can be attached to any Graph, Node, or Edge object, and is a List<VectorMetadata>. The embeddings within can be used for a variety of different vector searches (such as CosineSimilarity).

All of these properties can be used in conjunction with one another when filtering for retrieval.

Storing and Searching Labels

List<string> labels = new List<string> 
{
  "test",
  "label1"
};

graph.CreateNode(new Node { TenantGUID = tenant.GUID, Name = "Joel", Labels = labels });

foreach (Node node in graph.ReadNodes(tenant.GUID, graph.GUID, labels))
{
  Console.WriteLine(...);
}

Storing and Searching Tags

NameValueCollection nvc = new NameValueCollection();
nvc.Add("key", "value");

graph.CreateNode(new Node { TenantGUID = tenant.GUID, Name = "Joel", Tags = nvc });

foreach (Node node in graph.ReadNodes(tenant.GUID, graph.GUID, null, nvc))
{
  Console.WriteLine(...);
}

Storing and Searching Data

using ExpressionTree;

class Person 
{
  public string Name { get; set; } = null;
  public int Age { get; set; } = 0;
  public string City { get; set; } = "San Jose";
}

Person person1 = new Person { Name = "Joel", Age = 47, City = "San Jose" };
graph.CreateNode(new Node { TenantGUID = tenant.GUID, GraphGUID = graph.GUID, Name = "Joel", Data = person1 });

Expr expr = new Expr 
{
  "Left": "City",
  "Operator": "Equals",
  "Right": "San Jose"
};

foreach (Node node in graph.ReadNodes(tenant.GUID, graph.GUID, null, expr))
{
  Console.WriteLine(...);
}

Storing and Searching Vectors

It is important to note that vectors have a dimensionality (number of array elements) and vector searches are only performed against graphs, nodes, and edges where the attached vector objects have a dimensionality consistent with the input.

Further, it is strongly recommended that you make extensive use of labels, tags, and expressions (data filters) when performing a vector search to reduce the number of records against which score, distance, or inner product calculations are performed.

VectorSearchResult objects have three properties used to weigh the similarity or distance of the result to the supplied query:

Score - a higher score indicates a greater degree of similarity to the query
Distance - a lower distance indicates a greater proximity to the query
InnerProduct - a higher inner product indicates a greater degree of similarity to the query

When searching vectors, you can supply one of three requirements thresholds that must be met:

MinimumScore - only return results with this score or higher
MaximumDistance - only return results with distance less than the supplied value
MinimumInnerProduct - only return results with this inner product or higher

Your requirements threshold should match with the VectorSearchTypeEnum you supply to the search.

using ExpressionTree;

class Person 
{
  public string Name { get; set; } = null;
  public int Age { get; set; } = 0;
  public string City { get; set; } = "San Jose";
}

Person person1 = new Person { Name = "Joel", Age = 47, City = "San Jose" };

VectorMetadata vectors = new VectorMetadata 
{
  Model = "testmodel",
  Dimensionality = 3,
  Content = "testcontent",
  Vectors = new List<float> { 0.1f, 0.2f, 0.3f }
};

graph.CreateNode(new Node { Name = "Joel", Data = person1, Vectors = new List<VectorMetadata> { vectors } });

foreach (VectorSearchResult result in graph.SearchVectors(
  VectorSearchDomainEnum.Node,
  VectorSearchTypeEnum.CosineSimilarity,
  new List<float> { 0.1f, 0.2f, 0.3f },
  tenant.GUID,
  graph.GUID,
  null,  // labels
  null,  // tags
  null,  // filter
  10,    // topK
  0.1,   // minimum score
  100,   // maximum distance
  0.1    // minimum inner product
))
{
  Console.WriteLine("Node " + result.Node.GUID + " score " + result.Score);
}

Enumeration Ordering

A variety of EnumerationOrderEnum options are available when enumerating objects.

CreatedAscending - sort results in ascending order by creation timestamp
CreatedDescending - sort results in descending order by creation timestamp
NameAscending - sort results in ascending order by name
NameDescending - sort results in descending order by name
GuidAscending - sort results in ascending order by GUID
GuidDescending - sort results in descending order by GUID
CostAscending - for edges only, sort results in ascending order by cost
CostDescending - for edges only, sort results in descending order by cost
MostConnected - for nodes only, sort results in descending order by total edge count
LeastConnected - for nodes only, sort results in ascending order by total edge count

To enumerate, use the enumeration API for the resource you wish.

EnumerationQuery query = new EnumerationQuery
{
  Ordering = EnumerationOrderEnum.CreatedDescending,
  IncludeData = true,
  IncludeSubordinates = true,
  MaxResults = 5,
  ContinuationToken = null,         // set to the continuation token from the last results to paginate
  Labels = new List<string>,        // labels on which to match
  Tags = new NameValueCollection(), // tags on which to match
  Expr = null,                      // expression on which to match from data property
};

EnumerationResult result = graph.Node.Enumerate(query);
// returns
{
    "Success": true,
    "Timestamp": {
        "Start": "2025-06-22T01:17:42.984885Z",
        "End": "2025-06-22T01:17:43.066948Z",
        "TotalMs": 82.06,
        "Messages": {}
    },
    "MaxResults": 5,
    "ContinuationToken": "ca10f6ca-f4c2-4040-adfe-9de3a81b9f55",
    "EndOfResults": false,    // whether or not the end of the results has been reached
    "TotalRecords": 17,       // total number of matching records
    "RecordsRemaining": 12,   // records remaining should you enumerate again
    "Objects": [
        {
            "TenantGUID": "00000000-0000-0000-0000-000000000000",
            "GUID": "ebefc55b-6f74-4997-8c87-e95e40cb83d3",
            "GraphGUID": "00000000-0000-0000-0000-000000000000",
            "Name": "Active Directory",
            "CreatedUtc": "2025-06-21T05:23:14.100128Z",
            "LastUpdateUtc": "2025-06-21T05:23:14.100128Z",
            "Labels": [],
            "Tags": {},
            "Data": {
                "Name": "Active Directory"
            },
            "Vectors": []
        }, ...
    ]
}

Gathering Statistics

Statistics are available both at the tenant level and at the graph level.

Dictionary<Guid, TenantStatistics> allTenantsStats = graph.Tenant.GetStatistics();
TenantStatistics tenantStatistics = graph.Tenant.GetStatistics(myTenantGuid);

Dictionary<Guid, GraphStatistics> allGraphStatistics = graph.Graph.GetStatistics(myTenantGuid);
GraphStatistics graphStatistics = graph.Graph.GetStatistics(myTenantGuid, myGraphGuid);

REST API

LiteGraph includes a project called LiteGraph.Server which allows you to deploy a RESTful front-end for LiteGraph. Refer to REST_API.md and also the Postman collection in the root of this repository for details. By default, LiteGraph.Server listens on http://localhost:8701 and is only accessible to localhost. Modify the litegraph.json file to change settings including hostname and port.

Listening on a specific hostname should not require elevated privileges. However, listening on any hostname (i.e. using * or 0.0.0.0 will require elevated privileges).

$ cd LiteGraph.Server/bin/Debug/net8.0
$ dotnet LiteGraph.Server.dll

  _ _ _                          _
 | (_) |_ ___ __ _ _ _ __ _ _ __| |_
 | | |  _/ -_) _` | '_/ _` | '_ \ ' \
 |_|_|\__\___\__, |_| \__,_| .__/_||_|
             |___/         |_|

 LiteGraph Server
 (c)2025 Joel Christner

Using settings file './litegraph.json'
Settings file './litegraph.json' does not exist, creating
Initializing logging
| syslog://127.0.0.1:514
2025-01-27 22:09:08 joel-laptop Debug [LiteGraphServer] logging initialized
Creating default records in database litegraph.db
| Created tenant     : 00000000-0000-0000-0000-000000000000
| Created user       : 00000000-0000-0000-0000-000000000000 email: default@user.com pass: password
| Created credential : 00000000-0000-0000-0000-000000000000 bearer token: default
| Created graph      : 00000000-0000-0000-0000-000000000000 Default graph
Finished creating default records
2025-01-27 22:09:09 joel-laptop Debug [ServiceHandler] initialized service handler
2025-01-27 22:09:09 joel-laptop Info [RestServiceHandler] starting REST server on http://localhost:8701/
2025-01-27 22:09:09 joel-laptop Alert [RestServiceHandler]

NOTICE
------
LiteGraph is configured to listen on localhost and will not be externally accessible.
Modify ./litegraph.json to change the REST listener hostname to make externally accessible.

2025-01-27 22:09:09 joel-laptop Info [LiteGraphServer] started at 01/27/2025 10:09:09 PM using process ID 56556

Running in Docker

A Docker image is available in Docker Hub under jchristn/litegraph. Use the Docker Compose start (compose-up.sh and compose-up.bat) and stop (compose-down.sh and compose-down.bat) scripts in the Docker directory if you wish to run within Docker Compose. Ensure that you have a valid database file (e.g. litegraph.db) and configuration file (e.g. litegraph.json) exposed into your container.

Version History

Please refer to CHANGELOG.md for version history.

For Tasks:

Click tags to check more tools for each tasks

create graph find routes export data search vectors perform enumeration

For Jobs:

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