A startup from San Mateo, the United States that is founded by Emil Eifrem.
Graph DB
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.
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Check the traffic stats of neo4j on SimilarWeb. The key metrics to look for are: monthly visits, average visit duration, pages per visit, and traffic by country. Moreoever, check the traffic sources. For example "Direct" traffic is a good sign.
Check the "Domain Rating" of neo4j on Ahrefs. The domain rating is a measure of the strength of a website's backlink profile on a scale from 0 to 100. It shows the strength of neo4j's backlink profile compared to the other websites. In most cases a domain rating of 60+ is considered good and 70+ is considered very good.
Check the "Domain Authority" of neo4j on MOZ. A website's domain authority (DA) is a search engine ranking score that predicts how well a website will rank on search engine result pages (SERPs). It is based on a 100-point logarithmic scale, with higher scores corresponding to a greater likelihood of ranking. This is another useful metric to check if a website is good.
The latest comments about neo4j on Reddit. This can help you find out how popualr the product is and what people think about it.
The stack runs on Qdrant for vector storage, Ollama for local embeddings, and optional Neo4j for a knowledge graph that I added later. I also set it up to route different operations to the best LLM for each task. It provides eleven tools for your Claude Code instance to manage long-term memory operations, and your memories data never leaves your machine. - Source: dev.to / 5 months ago
Perhaps the biggest promoter of the term has been Philip Rathle from Neo4j, which offers the best-known graph database system for storing knowledge graphs. But here's where the confusion starts: Is a knowledge graph something you store, or is it how you store something? It's not just a knowledge graphโit's also a graph database. That distinction matters, but the boundaries are blurry. - Source: dev.to / 7 months ago
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 year ago
Neo4j is a leading graph database that is easy to use and powerful for knowledge graphs. - Source: dev.to / about 1 year ago
Neo4j is one of the most popular graph databases. It offers powerful querying capabilities through its Cypher query language. - Source: dev.to / over 1 year ago
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 / over 1 year ago
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 / almost 2 years ago
Neo4jโโโLeading graph database platform, known for its performance and scalability. - Source: dev.to / about 2 years ago
Neo4j is a graph database that represents and stores data using graph structures with nodes, edges, and properties. - Source: dev.to / about 2 years ago
Neo4j: An ACID-compliant graph database with a high-performance distributed architecture. Ideal for complex relationship and pattern analysis in domains like social networks. - Source: dev.to / over 2 years ago
The GenAI Stack came about through a collaboration between Docker, Neo4j, LangChain, and Ollama. The goal of the collaboration was to create a pre-built GenAI stack of best-in-class technologies that are well integrated, come with sample applications, and make it easy for developers to get up and running. The goal of the collaboration was to create a pre-built GenAI stack of best-in-class technologies that are... - Source: dev.to / almost 3 years ago
NoSQL is a term that we have become very familiar with in recent times and it is used to describe a set of databases that don't make use of SQL when writing & composing queries. There are loads of different types of NoSQL databases ranging from key-value databases like the Reddis to document-oriented databases like MongoDB and Firestore to graph databases like Neo4J to multi-paradigm databases like FaunaDB and... - Source: dev.to / almost 3 years ago
Recently I have taken an interest in big data. https://neo4j.com/ , https://cassandra.apache.org/ , https://clickhouse.com/, https://www.elastic.co/ - are all databases I have experience with. Neo4j and Cassandra only as a hobby, but Clickhouse I have used in production, and Elasticsearch I have used for some 7 years now. Source: about 3 years ago
For organizations and their applications that are designed to detect fraud, like International Consortium of Investigative Journalists, or try to improve customer experience via personalization, as in the case of Tourism Media, a NoSQL graph database like Neo4j is a good match. In these kinds of use cases, the quantity of data we're dealing with is enormous, and the pattern we're searching for in the data is often... - Source: dev.to / about 3 years ago
First, you need to choose a specific graph database platform to work with, such as Neo4j, OrientDB, JanusGraph, Arangodb or Amazon Neptune. Once you have selected a platform, you can then start working with graph data using the platform's query language. - Source: dev.to / over 3 years ago
Welcome to the world of graph databases! When it comes to modelling complex and highly connected data, graph databases have proven to be an efficient and intuitive solution. And one of the most popular graph databases out there is Neo4j, which uses a query language called Cypher. - Source: dev.to / over 3 years ago
First, privilege escalation would be a bit difficult without visibility of whose privilege level should be targeted. Of course, as mentioned previously, AD does offer the ability for an authorized domain user to simply query the data for information they're interested in like usernames, email addresses, group memberships, etc., which is one way that visibility could be obtained. However, we've seen that with a... - Source: dev.to / over 3 years ago
Recently, while working on a new feature for Neo4j GraphAcademy, I noticed an omission with the Neo4j JavaScript driver in TypeScript projects. - Source: dev.to / over 3 years ago
A graph database (something like Neo4j) seems like a case where NoSQL offers tangible advantages. Heirarchical/recursive queries aren't a strong point of relational databases. If I'm not mistaken, OG relational algebra didn't allow for recursion. Source: almost 4 years ago
For mutual friends, we can build a social graph for every user. Each node in the graph will represent a user and a directional edge will represent followers and followees. After that, we can traverse the followers of a user to find and suggest a mutual friend. This would require a graph database such as Neo4j and ArangoDB. - Source: dev.to / almost 4 years ago
I created Davraz for TigerGraph 2020 Graphathon. (It got 1st Place Reward YAAAY!) It is a tool for visualizing your TigerGraph and Neo4j databases. TigerGraph and Neo4j are graph databases. Usually, data is stored in SQL databases. Graph databases are a fairly new way to store data. - Source: dev.to / about 4 years ago
Neo4j, a prominent player in the field of graph databases, has garnered significant attention and discussion within the software industry, particularly in the context of data management and complex relationship modeling. Neo4j positions itself as an open-source graph database, implemented in Java, and is described as a fully transactional Java persistence engine that stores data structured as graphs rather than tables. This structural approach distinguishes it from traditional relational databases, making it particularly effective for analyzing complex networks and relationships.
Neo4j is widely recognized for its strong performance and scalability, which are critical attributes for enterprises that require robust data handling capabilities. The platform's querying abilities, powered by its Cypher query language, are frequently lauded for their strength, providing graph traversal and pattern matching capabilities that are not easily replicated by traditional SQL databases. This feature is particularly advantageous in domains requiring intricate relationship analysis, such as social networks and fraud detection.
In recognition of these capabilities, Neo4j is considered an industry leader in graph databases, frequently mentioned alongside or compared to other technologies such as Amazon Neptune, ArangoDB, and OrientDB. Its ease of use, particularly in building knowledge graphs, positions it as a valuable tool for developers and organizations looking to leverage graph data structures for more than just basic storage solutions.
Despite its strengths, Neo4j does exhibit certain limitations as noted in public discourse. A key point of consideration is its designation as a single-model graph database, meaning it supports solely graph data models and lacks multi-model capabilities. This limitation necessitates the use of additional database technologies for applications that also require document or key/value storage, a functionality offered by multi-model databases like ArangoDB.
The evolving landscape of database technologies also introduces new challengers and potential integrations. For example, discussions around retrieval augmented generation (RAG) techniques highlight how Neo4j can be paired with vector databases for applications requiring semantic similarity alongside entity relationships.
Neo4j's active community and consistent engagement in tech spaces reflect its reputable standing in the field. It is frequently included in various lists and guides, illustrating its broad acceptance as a premier graph database solution. Detailed tutorials, such as those for installing Neo4j on different platforms or building applications with the GenAI Stack, indicate ongoing developer support and a commitment to facilitating user onboarding and integration.
Overall, Neo4j's prominence in the graph database arena is both recognized and reinforced by its continued innovation, strong community, and practical applicability in complex data scenarios. Its position is bolstered by its ability to seamlessly model and query highly interconnected data, though future developments may necessitate enhancements in multi-model capabilities to maintain its competitive edge. As the demand for sophisticated data analysis grows, Neo4j remains a critical player in bringing efficient and powerful graph database solutions to the forefront of the industry.
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