Janakiram MSV (Jani) is a practicing architect, research analyst, and advisor to Silicon Valley startups. He focuses on the convergence of modern infrastructure powered by cloud-native technology and machine intelligence driven by generative AI.
To track and process rapidly changing data, developers frequently poll the database to respond to changes. For example, when multiple temperature sensors' telemetry data is ingested into a time-series database, a query must be run on a regular basis to track it. Similarly, an e-commerce application may need to trigger an event when a large transaction occurs. To track changes in both scenarios, the original database source must be polled on a regular basis.
Drasi takes a different approach to data collection by monitoring the logs generated by the database system. Every operation on a table, such as an insert, update, or delete, generates a log entry that is stored externally. Rather than querying the source, Drasi tracks changes using database logs. Because read operations are performed on log entries, the source database is less burdened.
It is worth noting that Microsoft has developed a platform for converting system logs and audit trails into a graph database and extending that to an event-driven environment. This opens up new opportunities for developers to create modern data processing systems based on large language models. Drasi has the potential to play an important role in RAG by providing real-time data changes as context for LLMs, enabling users and AI agents to make better decisions.
Microsoft Azure Graphdb Event-Driven
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