A naukri.com initiative
Amazon
1M
148
Image Credit: Amazon
How Coinbase provides trustworthy financial experiences through real-time user clustering with Amazon Neptune
- Coinbase migrated their user clustering system to Amazon Neptune Database to handle vast amounts of data related to transactions, user behavior, and market trends.
- The original datastore for the clustering system was not graph-based, and clusters needed to be precomputed and stored in a NoSQL database.
- Pre-calculating clusters became more challenging with increasing complexity over time and necessitated a high number of database updates to support each specific use case.
- Graph databases are designed to manage complex, interconnected data structures, allowing representation and querying of relationships between entities.
- Coinbase needed a solution that can handle frequent updates to both data and relationships, and graph database can perform real-time traversals of connections and relationships.
- Neptune Database addresses several technical challenges faced by large-scale graph database implementations. Because it is fully managed, Coinbase can eliminate significant operational overhead while providing flexibility in data modeling and querying.
- Coping with write-heavy workload characterized by frequent updates arising from multiple events, Coinbase micro batches into the same transaction achieving desired ingestion rates through 20 writes per second.
- Coinbase achieved new use cases, performance efficiency, reliability, cost optimization, and visualizations with 30% savings in storage costs by eliminating redundant information.
- Coinbase's journey with Neptune Database showcases the power of graph databases in solving complex, interconnected data challenges at scale.
- Neptune Analytics is a memory-optimized graph database that helps you find insights faster by analyzing graph datasets with built-in algorithms.
Read Full Article
8 Likes
For uninterrupted reading, download the app