How to get real-time insights from your JSON data?
summary
Couchbase Analytics runs real-time queries against native JSON with no ETL real-time JSON analytics, creating read-only shadow copies to isolate operational workloads and using an MPP engine to scale throughput across nodes. Python UDFs are uploaded as zip artifacts (example workflow: python UDFs packaged with shiv and uploaded via REST), then executed in parallel (one Python process per node controller) to run models like RoBERTa and scikit‑learn for sentiment. Feature status: works in developer preview with fencing and faster interpreter reuse planned; S3/Azure Blob external datasets supported.
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chapters (8)
- 0:00Introduction and speakers
- 1:02Couchbase data platform overview
- 3:51JSON analytics challenges
- 5:16Couchbase analytics solution
- 6:59Python UDFs for ML integration
- 13:57Demo of Python UDFs
- 26:40Q&A session
- 36:27Closing remarks and resources
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