Workloads
When deploying Memgraph in production, it is essential to consider a set of prerequisites to ensure optimal performance, scalability and resilience. That includes decisions about hardware configurations and integration strategies.
This section provides guides that are the starting point to production-readiness with Memgraph.
Before you dive into specific setups, it’s important to think about:
- Hardware requirements and instance sizing
- Driver configuration
- Flags when starting Memgraph
- Data import best practices
- Connecting to external sources
These factors ensure Memgraph performs effectively in your environment, no matter the use case.
How to use these guides
Start with the Deployment best practices. That page covers the best practices that apply to most production deployments, regardless of your workload type and are agnostic to specific use cases. Each separate guide in the Workloads section focuses on a particular type of workload or deployment scenario. At the beginning of each guide, you’ll learn when that use case is a good fit for your needs and specific tailored recommendations.
Recommendations in those guides override anything written in the general suggestions when there’s a conflict, so always defer to the targeted guide when applicable.
Available guides
Here are the currently available guides to help you deploy Memgraph effectively:
Memgraph in high-throughput workloads
Scale your write throughput while keeping up with fast-changing, high-velocity graph data.
Memgraph in GraphRAG use cases
Learn how to optimize Memgraph for Retrieval-Augmented Generation (RAG) systems using graph data.
🚧 Guides in construction
- Memgraph in transactional workloads
- Memgraph in analytical workloads
- Memgraph in mission critical workloads
- Memgraph in supply chain use cases
- Memgraph in cybersecurity use cases
- Memgraph in fraud detection use cases
If you’d like to help us prioritize this content, feel free to reach out on Discord!
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