Category Archives: Testing

Bullshit Graph Database Performance Benchmarks

Hey HackerNews, let me just drop my mixtape, checkout my soundcloud and “Death Row” is the label that pays me.

How is the Graph Database category supposed to grow when vendors keep spouting off complete bullshit? I wrote a bit about the ridiculous benchmark Memgraph published last month hoping they would do the right thing and make an attempt at a real analysis. Instead these clowns put it on a banner on top of their home page. So let’s tear into it.

At first I considered replicating it using their own repository, but it’s about 2000 lines of Python and I don’t know Python. Worse still, the work is under a “Business Source License” which states:

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Testing APOC inside your Stored Procedures

The Awesome Procedures on Cypher (APOC) plugin is packed with goodies to make your life working with Neo4j easier. Sometimes you want to use these goodies in your own stored procedures…and you want to be able to test them. So how do we go about doing that exactly?
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Vendor Benchmarks

How does the saying go? There are lies, damned lies, and benchmarks. I’ve already made my feelings about database vendor benchmarks known, but in case you missed it. They are complete fabrications. Never to be trusted, never ever. Never. But vendors love to do benchmarks, they love spreading fear, uncertainty and doubt instead of spending their time doing productive things like creating useful content that teaches people how to use their product. I wish I could just ignore this nonsense and focus on what really matters, like helping our customers to successful production rollouts, but alas, here we are.

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Building a Dating site with Neo4j – Part Two

We came up with an idea for a dating site and an initial model in Part One. Next we are going to work on a back end HTTP API, because I’m old school and that’s the way I like it. We will build our HTTP API right into Neo4j using an extension which turns Neo4j from a Server into a Service. Unlike last time where we wrote a clone of Twitter, I don’t really know where I’m going with this, so let’s start with some of the obvious API endpoints and then we can design and build more as we go along. Is this Agile or am I just being an idiot? I can’t tell, so onward we go.
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Our own Multi-Model Database – Part 3

shitty3

If you haven’t read part 1 and part 2 then do that first or you’ll have no clue what I’m doing, and I’d like to be the only one not knowing what I’m doing.

We’ve built the beginnings of this database but so far it’s just a library and for it to be a proper database we need to be able to talk to it. Following the Neo4j footsteps, we will wrap a web server around our database and see how it performs.

There are a ton of Java based frameworks and micro-frameworks out there. Not as bad as the Javascript folks, but that still leaves us with a lot of choices. So as any developer would do I turn to benchmarks done by other people of stuff that doesn’t apply to me, and you won’t believe what I found –scratch that, yes you will, I got benchmarks.
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Our own Multi-Model Database – Part 1

shittydb

I may be remembering this wrong, but I think it was Henry Rollins who once asked, “What came first, the shitty Multi-Model Databases or the Drugs?” His confusion was over whether:

A) there were a bunch of developers dicking around with their Mac laptops and they wrote a shitty database, put it on github, posted on hacker news, and then other developers who were on drugs started using it or…

B) there were a bunch of developers on ketamine and ecstasy and somebody said lets write a shitty database

I think “A” is what probably happens and how we end up with over 300 databases on DB Engines. But what about “B” ? Well I don’t have any good stuff lying around, but I did hurt my foot the other day and the doctors gave me some Tramadol, so lets down some of that and see what happens.
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Speeding up Traversals

roots

A few folks have come to us recently with the need to trace lineages of nodes of variable depth many hops away. You can run into this need if you are looking at the ancestries of living things, tracing data as it flows through an ETL, large network connectivity maps, etc. These types of queries tend to be murder on relational databases because of the massive recursive joins they have to deal with. Let’s give them a try in Neo4j.
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Scaling Cypher Writes

salt-pepa-writes

Let’s talk about writes, baby. Let’s talk about you and me. Let’s talk about all the good things. And the bad things that may be. Let’s talk about writes, and indexing and batching, and transactions in Neo4j. Let’s start with my environment. A 3 year old MacBook Pro (dying to get the new ones… once they finally come out) running a 4 core 2.3 GHz Intel Core i7 that is hyper-threading and pretending to have 8. An Apple SM256E SSD that is about average as far as SSDs go. So definitely not a production grade server, so bear that in mind.
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Benchmarks and Superchargers

Interceptor

For the most part, I hate competitive benchmarks. The vendor who publishes them always seems to come out on top regardless. The numbers are always amazing, but once you start digging in a little bit you start to see faults in what is actually being measured and it never applies to real world workloads. For example you have Cassandra claiming 1 Million writes per second on 300 servers. Then Aerospike claiming 1 Million writes per second on 50 servers. MongoDB claiming almost 32k writes per second on a single server, but claiming Cassandra can only do 6k w/s and Couch can only do 1.2k w/s on a single server… Then ScyllaDB has almost 2 Million writes per second on 3 servers blowing everybody away.
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Using the Testing Harness for Neo4j Extensions

harness

I’ve been creating both unit tests and integration tests for Neo4j Unmanaged Extensions for far too long. The Neo4j Testing Harness was introduced in version 2.1.6 to simplify our lives and just do integration tests. Let’s try it on and see just how awesome we look. First thing we need to do is add the dependency to our project:
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