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Tracking data changes (CDC) in QuestDB

Blog post from QuestDB

Post Details
Company
Date Published
Author
Javier Ramirez
Word Count
1,160
Company Posts That Month
6
Language
English
Hacker News Points
-
Post removed?
No
Summary

QuestDB is an open-source time-series database designed for high-performance workloads such as trading and mission control, offering ultra-low latency, high ingestion throughput, and multi-tier storage. It supports Parquet and SQL for data portability and AI readiness, facilitating tasks such as real-time data integrations, machine learning model updates, and table monitoring. QuestDB provides mechanisms for tracking data changes, such as the wal_transactions pseudo-table, which aids in Change Data Capture (CDC) for monitoring data ingestion, anomaly detection, and performance optimization. Although QuestDB cannot originate CDC directly, it can serve as a target using tools like Debezium. The wal_transactions table, a beta feature, helps track transaction metadata, but users must be cautious of its limitations and configuration requirements. The text highlights a sample repository that demonstrates how to use Python scripts to monitor table changes and dynamically materialize views, showcasing QuestDB's capabilities despite some limitations in query speed for large datasets. The QuestDB team is working on native materialized tables to enhance these functionalities, promising improvements in the near future.

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Real-time 5 2,676 708 189 +23%
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