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neo4j VS datarobot

Compare neo4j VS datarobot and see what are their differences

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Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

neo4j logo neo4j

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

datarobot logo datarobot

Become an AI-Driven Enterprise with Automated Machine Learning
  • neo4j Landing page
    Landing page //
    2023-05-09
  • datarobot Landing page
    Landing page //
    2023-08-01

neo4j

Website
neo4j.com
Pricing URL
Official neo4j Pricing
$ Details
Release Date
2007 January
Startup details
Country
United States
State
California
City
San Mateo
Founder(s)
Emil Eifrem
Employees
500 - 999
Edit details

datarobot

Website
datarobot.com
Pricing URL
-
$ Details
Release Date
2012 January
Startup details
Country
United States
State
Massachusetts
City
Boston
Founder(s)
Jeremy Achin
Employees
1,000 - 1,999
Edit details

neo4j features and specs

  • Graph DB

datarobot features and specs

  • Ease of Use
    DataRobot provides a user-friendly interface that makes it accessible for users with varying levels of expertise, from data scientists to business analysts.
  • Automated Machine Learning (AutoML)
    The platform automates the process of building, deploying, and maintaining machine learning models, significantly reducing the time and effort required.
  • Scalability
    DataRobot supports scalable machine learning workflows, allowing businesses to handle large datasets and complex computations efficiently.
  • Integration
    DataRobot offers seamless integration with popular data platforms and tools like AWS, Azure, BigQuery, and Snowflake, facilitating smooth data pipeline management.
  • Model Interpretability
    The platform provides various tools and visualizations for understanding and interpreting model predictions, which is crucial for decision-making and regulatory compliance.
  • Collaboration Features
    DataRobot includes collaboration tools that allow teams to work together on projects, share insights, and ensure consistency across different stages of the machine learning lifecycle.

Possible disadvantages of datarobot

  • Cost
    DataRobot can be expensive, especially for small businesses or startups with limited budgets, potentially making it inaccessible for some companies.
  • Complexity for Advanced Users
    While the platform is user-friendly, advanced users might find it restrictive because they may prefer more control and customization over their machine learning workflows.
  • Steep Learning Curve for Non-Data Scientists
    Despite being user-friendly, non-data scientists may still face a learning curve to fully leverage the platform's capabilities and understand the underlying machine learning principles.
  • Dependency on Cloud Services
    DataRobot's heavy reliance on cloud services can be a limiting factor for organizations with strict data governance policies that require on-premise solutions.
  • Limited Algorithm Choices
    While DataRobot supports a wide range of algorithms, it might not include certain niche models or the latest advancements in machine learning algorithms, which could be a limitation for specific use cases.
  • Data Privacy Concerns
    Handling sensitive data on a third-party platform can raise privacy concerns for some organizations, particularly those in highly regulated industries.

Analysis of neo4j

Overall verdict

  • Yes, Neo4j is generally regarded as a good choice for applications where understanding and leveraging relationships between data points is crucial. Its mature ecosystem, active community, and extensive documentation further enhance its credibility and usability.

Why this product is good

  • Neo4j is considered a leading graph database platform that is highly effective for storing and querying complex data relationships. It is appreciated for its powerful query language, Cypher, useful for handling connected data. Its graph model is intuitive for users to understand and map to real-world applications, making it popular for use cases such as social networking, recommendation engines, and fraud detection.

Recommended for

  • Social network analysis
  • Recommendation systems
  • Fraud detection
  • Network and IT operations
  • Knowledge graphs
  • Data lineage tracking

neo4j videos

+ Add

All about GRAND Stack: GraphQL, React, Apollo, and Neo4j

More videos:

  • Review - Kevin Van Gundy | Building a Recommendation Engine with Neo4j and Python

datarobot videos

+ Add

Build and Deploy a Managed Machine Learning Project in 10 minutes - Scott Lutz (DataRobot)

More videos:

  • Review - How DataRobot Works
  • Review - DataRobot Predictions Using Alteryx

Category Popularity

0-100% (relative to neo4j and datarobot)

neo4j

datarobot

Databases
100 100%
Databases
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Graph Databases
100 100%
Graph Databases
0% 0
Business & Commerce
0 0%
Business & Commerce
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare neo4j and datarobot

neo4j Reviews

Top 15 Free Graph Databases
Neo4j is an open-source graph database, implemented in Java described as embedded, disk-based, fully transactional Java persistence engine that stores data structured in graphs rather than in tables. Neo4j Community Edition
Source: www.predictiveanalyticstoday.com
ArangoDB vs Neo4j - What you can't do with Neo4j
Multi-Model: Neo4j is a single-model graph database. It does not support any other data models. If your application requires a document or key/value store, you would have to use a second database technology to support it. Being multi-model, ArangoDB allows you to not only use one database for everything,but run ad hoc queries on data stored in different models.
Source: www.arangodb.com

datarobot Reviews

The 16 Best Data Science and Machine Learning Platforms for 2021
Description: DataRobot offers an enterprise AI platform that automates the end-to-end process for building, deploying, and maintaining AI. The product is powered by open-source algorithms and can be leveraged on-prem, in the cloud or as a fully-managed AI service. DataRobot includes several independent but fully integrated tools (Paxata Data Preparation, Automated Machine...
Source: solutionsreview.com

Social recommendations and mentions

Based on our record, neo4j seems to be a lot more popular than datarobot. While we know about 34 links to neo4j, we've tracked only 1 mention of datarobot. 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.

neo4j mentions (34)

  • 6 retrieval augmented generation (RAG) techniques you should know
    The key difference lies in the retrieval mechanism. Vector databases focus on semantic similarity by comparing numerical embeddings, while graph databases emphasize relations between entities. Two solutions for graph databases are Neptune from Amazon and Neo4j. In a case where you need a solution that can accommodate both vector and graph, Weaviate fits the bill. - Source: dev.to / about 1 month ago
  • LLM to extract and auto generate knowledge graph - step by step, in ~100 lines of python
    Neo4j is a leading graph database that is easy to use and powerful for knowledge graphs. - Source: dev.to / about 1 month ago
  • 10 Ways AI Can Speed Up your Mobile App Development
    Neo4j is one of the most popular graph databases. It offers powerful querying capabilities through its Cypher query language. - Source: dev.to / 3 months ago
  • Databases in 2024: A Year in Review
    Great heads up. I wonder about graph databases. He mentioned and both include the graph use case and I wonder how they compare to . - Source: Hacker News / 5 months ago
  • Installing Neo4j In Ubuntu
    The first blog in this series is to install neo4j - desktop version and few plugins which would help us to build an application. I am using Ubuntu 22.04.4 LTS. - Source: dev.to / 10 months ago
View more

datarobot mentions (1)

  • Predicting the End of Season Bundesliga Table
    To predict what we would have expected, we used the models and approach we developed to predict the knockout stage of the Champions League using data provided by Data Sports Group.  We used DataRobot’s models to predict which team would win each match to simulate the final nine matchdays 10,000 times.  For each team, we calculated the average number of wins, draws and losses over those 10,000 seasons to build an... Source: about 2 years ago

What are some alternatives?

When comparing neo4j and datarobot, you can also consider the following products

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

Dataiku - Dataiku is the developer of DSS, the integrated development platform for data professionals to turn raw data into predictions.

Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.

RapidMiner - RapidMiner is a software platform for data science teams that unites data prep, machine learning, and predictive model deployment.

OrientDB - OrientDB - The World's First Distributed Multi-Model NoSQL Database with a Graph Database Engine.

H2O.ai - Democratizing Generative AI. Own your models: generative and predictive. We bring both super powers together with h2oGPT.

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