Hello everyone!
In this blog series, we’re going to explore various graph databases for a Golang project I’m currently working on.
The project requires a cloud-native graph database.
Our use case involves a small schema with a massive amount of data, millions of new edges inserted daily, and sub-second query times for interactive user engagement.
We will talk more about the schema in the next post.
Over the following days, we’ll dive into different graph databases, test installations, code samples, and benchmark results. We’ll kick off our journey with four popular graph databases: EdgeDB, Neo4J, and Dgraph.
Let’s start with a brief overview of our project requirements and the plan for the upcoming blog posts:
Project Requirements:
- Cloud-native graph database
- Quite small schema with a huge amount of data
- Data-intensive for writing, tens million of new edges daily
- Sub-second query times for reading, interactive user engagement
Approximate plan:
- Task description and plan (today’s post)
- Schema discussion and data modeling
- Diving into EdgeDB
- Evaluating Neo4J
- Assessing Dgraph
- Considering other options.
By the end of the series, we’ll have a deeper understanding of the strengths and weaknesses of each option, and ultimately make an informed decision on the best fit for our Golang project.
Now, I’d love to hear from you! What are your favorite graph databases, and why? If there’s a specific database you’d like us to consider, please let us know in the comments below. I’m open to suggestions and eager to learn from your experiences.
