How we solved for Aggregation, Search and Time Series Big Data usecases using Elasticsearch Database
summary
QuickBooks Online builds search, aggregation and time-series on Elasticsearch with Kafka for ingestion and AWS Elasticsearch as managed hosting, achieving 24 nodes and about 20,000 TPS indexing with <10 ms indexing latency. Design decisions include company-ID routing to pin shards, edge n-grams and custom analyzers for typeahead, index-vs-query tradeoffs (index customer name into invoices), batching for 10x throughput, frequent reindexing and rollover/ultrawarm for time-based retention.
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chapters (5)
- 0:00Introduction and architecture
- 4:01Core design principles
- 7:24Implementing universal search
- 19:32Data aggregation strategies
- 27:06Time series and Q&A
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