Neo4j VS NebulaGraph Database

Neo4j: An ACID-compliant graph database with a high-performance distributed architecture. Ideal for complex relationship and pattern analysis in domains like social networks.

After spending millions fighting the committer of ONgDB who removed the commons clause from the AGPL branded license, it looks like the Free Software Foundation got involved and forced them to remove the commons clause or change the license to their own proprietary license.

https://github.com/neo4j/neo4j/commit/b6237ca4e31706b1efbd0f...

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 well integrated, come with sample applications, and make it easy for developers to get up and running.

Neo4j (GraphQL)

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 Cassandra.

this thread on this github issue could be useful.

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.

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 complex.

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.

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.

A NoSQL graph database is a type of non-relational, distributed database which employs a graph model. NoSQL stands for “Not only SQL” and refers to a new breed of databases that differ from traditional relational databases in their data model and performance. Graph databases are especially useful for data associated with relationships—everything from friendships on social netwo#rks to equipment supply chains or business processes. They can quickly traverse vast amounts of linked data points to discover insights and hidden connections between entities, making them ideal for network analysis– such as financial fraud detection, recommendation engines and many other use cases– all while performing at scale.

An open source graph database is always the best place to start as they come with a supportive community that ultimately creates the perfect ecosystem.

When we first came across NebulaGraph, because the ecology was not perfect, and only some businesses migrated to Nebula, we used to import NebulaGraph data, whether full or incremental, by pushing Hive tables to Kafka and consuming Kafka to write NebulaGraph in batch. Later, as more and more data and businesses switched to NebulaGraph, the problem of importing data efficiency became more and more serious. The increase in import time made it unacceptable to still be importing data at full volume during peak business hours.

NebulaGraph NebulaGraph is a popular open-source graph database that can handle large volumes of data with milliseconds of latency, scale up quickly, and have the ability to perform fast graph analytics. Official website https://www.nebula-graph.io/ GitHub projects https://github.com/orgs/vesoft-inc/repositories https://github.com/vesoft-inc/nebula

NebulaGraph, a leading open source graph database, announced it raised tens of millions of US dollars in Series A funding. Investors in the round are led by Jeneration Capital, with participation from the previous investors - Matrix Partner China, Redpoint China Ventures, and Source Code Capital. China Renaissance served as the exclusive financial advisor in this financing round.

Support backup and restore. https://github.com/vesoft-inc/nebula/pull/3469 https://github.com/vesoft-inc/nebula-agent/pull/1 https://github.com/vesoft-inc/nebula-br/pull/22

One option is NebulaGraph if your looking for low latency, scalability, and HA.

After the step-by-step decomposition of the patterns, the expected execution plan for the MATCH clause is finally generated. As you can see, it takes a lot of effort to transform a complicated pattern into the underlying interfaces for a traversal. Of course, the execution plan can be optimized, such as the multi-step traversal can be encapsulated by using the Loop operator and the sub-plan of a one-step traversal can be reused, which will not be detailed in this article. If you are interested, please refer to the source code of Nebula Graph.