Julian's Polymath Explorations

(UPDATED May 2024)   Now that we have discussed a full technology stack based on Neo4j (or other graph databases), and that we a design and implementation available from the open-source project BrainAnnex.org  , what next?  What shall we build on top? Well, how about  Full-Text Search ?  This article is part of a growing, ongoing series on Graph Databases and Neo4j Full-Text Searching/Indexing The Brain Annex open-source project includes an implementation of a design that uses the convenient services of its Schema Layer , to provide indexing of word-based documents using Neo4j. The python class FullTextIndexing ( source code ) provides the necessary methods, and it can parse both plain-text and HTML documents (for example, used in "formatted notes"); parsing of PDF files and other formats will be added at a later date. No grammatical analysis ( stemming or lemmatizing ) is done on the text.  However, a long list of common word ("stop ...

Putting it All Together : a Technology Stack on top of a (Neo4j) Graph Database (UPDATED June 2024)  For many practical use cases, one needs a full data-management solution, not just a database.   So, armed with the Schema Layer discussed in the previous part , the next natural step is to add a web API and possibly a User Interface . This article is part of a growing,  ongoing  series  on Graph Databases and Neo4j   The Web API Layer / Data Manager The Web API Layer ("Data Manager")  is in some ways the most straightforward layer - because the "heavy lifting" is done by the Schema Layer.   I've been involved in projects that utilized an inadequate Schema Layer - and in those situations the API Layer ends up taking on an immense amount of responsibility that don't logically belong there; the end result being a lot of difficult, error-prone and non-modular development that feels like "pulling teeth"! By contrast, with a...

(UPDATED MAY 2026).   So, you want to build a python app or Jupyter notebook to utilize Neo4j, but aren't too keen on coding a lot of string manipulation to programmatic create ad-hoc Cypher queries?   You're in the right place: the GraphAccess library (formerly called NeoAccess) can do take care of all that, sparing you from lengthy, error-prone development that requires substantial graph-database and software-development expertise! This article is part 4 of a growing,  ongoing  series  on Graph Databases and Neo4j   "GraphAccess" is the bottom layer of the technology stack provided by the BrainAnnex open-source project .  All layers are very modular, and the GraphAccess library may also be used by itself , entirely separately from the rest of the technology stack.  (A diagram of the full stack is shown later in this article.) GraphAccess interacts with the Neo4j Python driver , which is provided by the Neo4j company, to acce...

You have a general idea of what Graph Databases - and Neo4j in particular - are...  But how to get started?  Read on! This article is part 3 of a growing,  ongoing  series  on Graph Databases and Neo4j   If you're new to graph databases, please check out part 1 for an intro and motivation about them.  There, we discussed an example about an extremely simple database involving actors, movies and directors...  and saw how easy the Cypher query language makes it to answer questions such as "which directors have worked with Tom Hanks in 2016" - questions that, when done with relational databases and SQL, turn into a monster of a query and an overly-complicated data model involving a whopping 5 tables! In this tutorial, we will actually carry out that query - and get acquainted with Cypher and the Neo4j browser interface in the process.  This is the dataset we'll be constructing: Get the database in place If you don't already have a datab...

UPDATED Feb. 2024 - Graph databases have an easygoing laissez-faire attitude: "express yourself (almost) however you want"... By contrast, relational databases come across with an attitude like a micro-manager:  "my way or the highway"... Is there a way to take the best of both worlds and distance oneself from their respective excesses, as best suited for one's needs?  A way to marry the flexibility of Graph Databases and the discipline of Relational Databases? This article is part 5 of a growing,  ongoing  series  on Graph Databases and Neo4j Let's Get Concrete Consider a simple scenario with scientific data such as the Sample, Experiment, Study, Run Result , where Samples are used in Experiments, and where Experiments are part of Studies and produce Run Results.  That’s all very easy and intuitive to represent and store in a Labeled Graph Database such as Neo4j .   For example, a rough draft might go like this:   The “labels” (b...