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Culture and Methodologies
Agile Career Development Methodologies Team Management
Data Engineering
AI/ML Big Data Data Databases IoT
Software Design and Architecture
Cloud Architecture Containers Integration Microservices Performance Security
Coding
Frameworks Java JavaScript Languages Tools
Testing, Deployment, and Maintenance
Deployment DevOps and CI/CD Maintenance Monitoring and Observability Testing, Tools, and Frameworks

The software you build is only as secure as the code that powers it. Learn how malicious code creeps into your software supply chain.

Apache Cassandra combines the benefits of major NoSQL databases to support data management needs not covered by traditional RDBMS vendors.

Generative AI has transformed nearly every industry. How can you leverage GenAI to improve your productivity and efficiency?

Modernize your data layer. Learn how to design cloud-native database architectures to meet the evolving demands of AI and GenAI workloads.

Benchmarking Graph Analytics Systems

The world’s most innovative companies use graph databases to achieve real-time data insight for critical use cases like fraud detection, recommendation engines, AI and machine learning, and customer 360. But not all graph databases are created equally. Unlike traditional graph databases, TigerGraph can scale for real-time multi-hop queries spanning trillions of relationships. This graph database benchmark study examines the data loading and query performance of TigerGraph, Neo4j, Amazon Neptune, JanusGraph, and ArangoDB. TigerGraph is 2x to more than 8000x faster at graph traversal and query response times compared to other graph databases tested, running on a single server.

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