Real-Time Analytics

Hacker News is a website that contains content from the tech industry and to find yourself among its most popular posters sometimes seems a miracle! To break the mystery around it, I tried to knowledge-hack it with Kafka and PageRank algorithm - read on to find out what I discovered!

Building real-time analytical applications require capable infrastructure. Picking the right software infrastructure components can take time and effort. When it comes to graph databases, find out why Memgraph is a fast and powerful real-time graph database.

Data lineage helps you make informed decisions that reduce costs, streamline operations and power innovation. Discover how stream tech helps with automatically mapping data lineage, and learn how Memgraph integrates with event streaming platforms.

Find vulnerabilities and security issues, or perform any other data analysis in your Identity and Access Management system with Memgraph, and ensure you are running a smooth operation.

Always wanted to identify the most influential developer within your GitHub network? Check out how by using PageRank.

Movie ratings from MovieLens are incoming, but you are still not sure what to watch over the weekend? Create your own movie recommendation system.

Recommending books is hard. Thanks to the Amazon books dataset and insights from graph analytics, you can build your own. Here’s how.

Analyze the Art Blocks transaction data, projects and communities in real-time with Memgraph

Some use cases in data analysis require near-instantaneous processing of data. To make it happen, you need tools for real-time data analysis that support the use of continuous queries.

A streaming database is a real-time data repository specifically designed to store, accumulate, process and enhance a data stream.

Real-time graph analytics combines streaming data technology, graph databases, and graph algorithms to tackle problems not suited for relational databases and batch processing.

Stream processing is a type of big data architecture in which the data is analyzed in real-time

In this article, you can learn the difference between stream processing vs batch processing, and get to know the basic use cases for each.

Learn more about the benefits of real-time analytics and how they allow you to get key insights almost instantaneously.

Learn how to use the GQLAlchemy library to manage data streams and database triggers in Memgraph

Learn about the differences between static and dynamic data, real-time data sources and ways of analyzing streaming data

Learn how to pick the best streaming analytics tool for your use case

Explore a network of retweets using a dynamic PageRank algorithm and a graph database

Discover how to detect communities in dynamic networks quickly with LabelRankT

An in-depth guide to understanding the dynamic node2vec algorithm and its advantages over static algorithms on streaming data

Learn the theory behind how to deal with streaming graph data by using Dynamic PageRank

Learn how to connect to a Pulsar cluster, create an Art Blocks NFT database in Memgraph and analyze streaming sales

A basic overview of the architecture and features offered by Apache Pulsar and Apache Kafka

Through this tutorial, you will learn how to connect to a Redpanda stream from Memgraph and analyze the graph data

A short story about working with librdkafka

Learn how to get Twitch data, find the most interesting statistics from the Twitch network and visualize the output of different MAGE algorithms on ingested data in real-time

Learn how to get Twitch data, find the most interesting statistics from the Twitch network and visualize the output of different MAGE algorithms on ingested data in real-time

Learn how to scrape Twitch data, find the most interesting statistics from the Twitch network and visualize the output of different graph algorithms

Check out what it takes to develop a recommendation engine with graph analytics

Learn how to ingest Reddit data, visualize it as a graph and perform sentiment analysis.