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by asteroidtunnel
145 days ago
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When I search for "high performance analytical database" in Bing, Ai summarized results are ClickHouse, Apache Druid, Singlestore, Couchbase, and Apache Pinot are considered among the best databases for real-time analytics due to their low query latency and high performance. In Google, Ai summarized results are ClickHouse, StarRocks, Snowflake, and Google BigQuery. Clickhouse is there in both of them and Exasol is not mentioned. If these claims were relevant, why is it not in the limelight? Clickhouse is known to ingest and analyze massive volumes of time-series data in real-time. How good is Exasol for this use case? |
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Apache Pinot, Druid and Clickhouse are designed for low-latency analytical queries at high concurrency with continuous ingestion. Pinot is popular because of it's native integration with streaming systems like Kafka, varied indexing, and it's ability to scale efficiently. They're widely used in observability and user-facing analytics – which are how “real-time analytics databases” are commonly perceived today.
Exasol (and SingleStore, Snowflake, BigQuery, etc) are more focused on enterprise BI and complex SQL analytics rather than application serving, or ultra-high ingest workloads. It performs well for structured analytical queries and joins, but it’s less commonly deployed with the user-facing analytics or high volume usage.
A good rundown from Tim Berglund in this video here: https://startree.ai/resources/what-is-real-time-analytics/