Software Alternatives, Accelerators & Startups
Register | Login

NetworkX VS TigerGraph DB

Compare NetworkX VS TigerGraph DB and see what are their differences

Flagsmith
Flagsmith lets you manage feature flags and remote config across web, mobile and server side applications. Deliver true Continuous Integration. Get builds out faster. Control who has access to new features. We're Open Source. featured
Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

NetworkX logo NetworkX

NetworkX is a Python language software package for the creation, manipulation, and study of the...

TigerGraph DB logo TigerGraph DB

Application and Data, Data Stores, and Graph Database as a Service
  • NetworkX Landing page
    Landing page //
    2023-09-14
  • TigerGraph DB Landing page
    Landing page //
    2023-08-29

NetworkX features and specs

  • Ease of Use
    NetworkX provides a simple and intuitive API that makes it easy for both novices and experienced users to create, manipulate, and study the structure and dynamics of complex networks.
  • Comprehensive Documentation
    The library is well-documented with a vast number of examples and tutorials, aiding users in understanding and applying the features effectively.
  • Rich Functionality
    NetworkX offers numerous built-in functions to analyze network properties, perform algorithms like shortest path and clustering, and handle various graph types such as directed, undirected, and multigraphs.
  • Integration with Python Ecosystem
    Being a Python library, NetworkX integrates seamlessly with other scientific computing libraries like NumPy, SciPy, and Matplotlib, allowing for extensive data analysis and visualization.
  • Active Community
    NetworkX's active community of users and developers means continuous improvements and updates, as well as a wealth of shared knowledge and code to draw upon.

Possible disadvantages of NetworkX

  • Performance Limitations
    NetworkX may suffer from performance issues with extremely large graphs due to its in-memory data storage and Python's inherent single-threaded execution, making it less suitable for handling very large-scale networks.
  • Lack of Parallel Processing
    NetworkX does not natively support parallel processing within its operations, which can be a drawback when working with complex computations or very large graphs.
  • Memory Consumption
    Graphs and network data structures in NetworkX may consume a substantial amount of memory, especially with large datasets, potentially leading to inefficiencies.
  • Visualization Limitations
    While NetworkX provides basic plotting capabilities, for more advanced and interactive visualizations, additional libraries like Matplotlib or Plotly might be needed.
  • Scalability Constraints
    The library is not designed to work efficiently with very large networks compared to other frameworks specialized for scalability, such as Graph-tool or igraph.

TigerGraph DB features and specs

No features have been listed yet.

NetworkX videos

+ Add

Directed Network Analysis - Simulating a Social Network Using Networkx in Python - Tutorial 28

TigerGraph DB videos

No TigerGraph DB videos yet. You could help us improve this page by suggesting one.

Add video

Category Popularity

0-100% (relative to NetworkX and TigerGraph DB)

NetworkX

TigerGraph DB

Graph Databases
64 64%
Graph Databases
36% 36
Databases
61 61%
Databases
39% 39
NoSQL Databases
64 64%
NoSQL Databases
36% 36
Developer Tools
0 0%
Developer Tools
100% 100

User comments

Share your experience with using NetworkX and TigerGraph DB. For example, how are they different and which one is better?
Log in or Post with

Social recommendations and mentions

Based on our record, NetworkX seems to be more popular. It has been mentiond 35 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

NetworkX mentions (35)

  • Representing Graphs in PostgreSQL
    If you are interested in the subject, also take a look at NetworkDisk[1] which enable users of NetworkX[2] which maps graphs to databases. [1] https://networkdisk.inria.fr/ [2] https://networkx.org/. - Source: Hacker News / 3 months ago
  • Build the dependency graph of your BigQuery pipelines at no cost: a Python implementation
    In the project we used Python lib networkx and a DiGraph object (Direct Graph). To detect a table reference in a Query, we use sqlglot, a SQL parser (among other things) that works well with Bigquery. - Source: dev.to / over 1 year ago
  • Custom libraries and utility tools for challenges
    If you program in Python, can use NetworkX for that. But it's probably a good idea to implement the basic algorithms yourself at least one time. Source: over 1 year ago
  • Google open-sources their graph mining library
    For those wanting to play with graphs and ML I was browsing the arangodb docs recently and I saw that it includes integrations to various graph libraries and machine learning frameworks [1]. I also saw a few jupyter notebooks dealing with machine learning from graphs [2]. Integrations include: * NetworkX -- https://networkx.org/ * DeepGraphLibrary -- https://www.dgl.ai/ * cuGraph (Rapids.ai Graph) --... - Source: Hacker News / over 1 year ago
  • org-roam-pygraph: Build a graph of your org-roam collection for use in Python
    Org-roam-ui is a great interactive visualization tool, but its main use is visualization. The hope of this library is that it could be part of a larger graph analysis pipeline. The demo provides an example graph visualization, but what you choose to do with the resulting graph certainly isn't limited to that. See for example networkx. Source: almost 2 years ago
View more

TigerGraph DB mentions (0)

We have not tracked any mentions of TigerGraph DB yet. Tracking of TigerGraph DB recommendations started around Mar 2021.

What are some alternatives?

When comparing NetworkX and TigerGraph DB, you can also consider the following products

neo4j - Meet Neo4j: The graph database platform powering today's mission-critical enterprise applications, including artificial intelligence, fraud detection and recommendations.

ArangoDB - A distributed open-source database with a flexible data model for documents, graphs, and key-values.

FalkorDB - Build Fast and Accurate GenAI Apps with GraphRAG at Scale

JanusGraph - JanusGraph is a scalable graph database optimized for storing and querying graphs.

Azure Cosmos DB - NoSQL JSON database for rapid, iterative app development.

RedisGraph - A high-performance graph database implemented as a Redis module.

Loading...