#graph databases

Now that the reblog apocalypse has been avoided for now - let’s talk a little about the use case of “I want a reblog within the chain to get the quote unquote appropriate recognition it deserves”.

This got me thinking about a reply from tumblr staff about the usage of the reblog graph. Honestly, I would love to know what is being used behind the scenes to generate this app (is this just React.js/Vis.js that queries the underlying relational databases with a limit clause and eventually after someone presses “get more nodes” it eventually breaks their browser? I digress).

In any case, let’s talk about the “requirements” that I saw come back from my dash regarding the issues with the now rolled-back reblog update. Of course, this is based on a super small sample size and does not encompass the breath and depth of what has been brought up to the staff. But just for funsies:

The original poster (OP) should be able to receive “metrics” (number of reblogs) of their post.

The original poster (OP) should be able to receive all comments / tags from reblogs of their post.

The current block mechanism is a non-negotiable. A blocked user should not be able to reblog or comment on a post by an OP that has blocked them.

Under the cut, let’s answer the question, what can we do with reblog graph and can it address the “reblog chain” use case the staff wants “solve”? Short answer is yes. And we can solve this fairly simply with the very limited information that I have.

At the core of it, Graph visualizations and databases are meant to help uncover relationships such as the potential influence of a particular reblog or help discover at which point did a post become viral. It could also be used as a discovery mechanism (e.g, I like this particular post, what other similar posts should be suggested? How many of my mutuals reblogged a similar post?) But, for the average user and the utility to assess the notes and comments of a post or subsequent reblogs? this is not the right use case and place for it.

Common challenges I hope has already been tested is the possibility for “dense nodes”. These are posts with thousands potentially millions of reblogs, which isn’t uncommon for heritage posts. Will this affect the latency of the users’s browser? I did see that they also cap the number of nodes shown on the graph, which is a necessary requirement for visualization/latency reasons. However, does this break some of the utility of a graph visualization or graph in the first place if not everything can be shown?

I admit, I don’t have the full use case, persona docs, behind this, any unit tests, data points, etc etc to make an informed comment about how the reblog graph was developed and why it was chosen for it’s purpose, but from experience? There are a heck of a lot better databases for designing a blog (e.g., Key-Value stores). A graph database and visualization for retrieving notes/tags is not one of them.

As noted in the European Union’s list of significant company acquisitions, Apple has acquired graph database maker Kuzu, Inc. The EU classifies an acquisition as “significant” not based on the company’s size, but on whether it involves providing core platform services. Kuzu was founded in Ontario in 2023 and had approximately ten employees at the time of the acquisition. The company’s website has…

For decades, relational databases have been the cornerstone of data storage and management. But as the world becomes increasingly interconnected and data volumes explode, the limitations of these traditional systems are becoming increasingly apparent. Enter graph databases: a new breed of technology poised to revolutionize how we store, analyse, and understand complex relationships within our data.

From Tables to Networks:

Imagine data as a vast, interconnected network. Relational databases, with their rigid rows and columns, struggle to capture the true essence of this network. They force data into pre-defined structures, often losing valuable information about the connections between different entities.

Graph databases, on the other hand, embrace the inherent network structure of data. They represent data points as nodes and the relationships between them as edges, forming a flexible and dynamic data model. This allows for a more intuitive and natural way to store and query information, particularly for data with intricate relationships, such as social networks, financial transactions, and supply chains.

Unveiling Hidden Insights:

The power of graph databases lies in their ability to reveal hidden patterns and connections within data. Traditional queries in relational databases often require complex joins and aggregations, making it difficult to uncover these hidden insights. With graph databases, however, traversing relationships becomes effortless.

Imagine exploring telco billing data. With a graph database, No more wading through mountains of disconnected billing data. Graph databases bring order to the chaos, presenting a clear picture of how customers, services, and charges are interrelated. Uncover hidden trends, optimize pricing models, and deliver personalized billing experiences all through the power of intuitive data connections.

Real-World Applications:

Graph databases are already transforming industries across the board. Here are some real-world examples:

Telecommunications: Graph databases power the invisible hand of modern telecom. It can be used to boost personalized offerings, analysing fraud calls, untangle subscriber networks and optimize service delivery.

Fraud Detection: Banks and financial institutions use graph databases to identify patterns in fraudulent transactions, preventing financial losses and protecting customer data.

Recommendation Engines: E-commerce platforms and media streaming services leverage graph databases to personalize product recommendations and content suggestions, enhancing user engagement and satisfaction.

Drug Discovery: Pharmaceutical companies utilize graph databases to analyse complex biological interactions, accelerating the development of new drugs and treatments.

Supply Chain Management: Organizations can use graph databases to optimize logistics and inventory management, ensuring efficient and cost-effective delivery of goods and services.

The Future is Graph-Powered:

As the world becomes increasingly interconnected and data-driven, the need for flexible and scalable data management solutions becomes ever more critical. Graph databases, with their unique characteristics and ability to handle complex relationships, are poised to become the leading technology for a future where data is king.

This is not to say that relational databases will become obsolete. Instead, they will likely coexist with graph databases, each playing a specific role in the data management ecosystem. Relational databases will remain valuable for structured data with well-defined relationships, while graph databases will shine for complex, interconnected data with dynamic relationships.

Embracing the Graph Revolution:

Whether you're a seasoned data scientist or just starting your data journey, understanding the power of graph databases is crucial for navigating the evolving landscape of data management. By embracing this new technology, you can unlock hidden insights, drive innovation, and make informed decisions that will propel your business towards success.

So, what are you waiting for? Start exploring the world of graph databases today and discover how they can revolutionize your approach to data and unlock the full potential of your digital information assets. Reach out to us at [email protected] to begin a dialogue that will craft the perfect graph database designs to meet your distinct requirements.

For More Information:-

Neo4j nabs $80M Series E as graph database tech flourishes

Neo4j has helped popularize the graph database. Today it was rewarded with an $80 million Series E to bring their products to a wider market in what could be the company’s last private fundraise.

The round was led by One Peak Partners and Morgan Stanley Expansion Capital with participation from existing investors Creandum, Eight Roads and Greenbridge Partners. Today’s investment exactly doubles…