This final article completes our tour of array capabilities. We’ll survey functions for array map and reduce operations, demonstrating behavior and commenting on performance. This is an opportunity to dig further into lambdas, which are critical for using arrays effectively.
ClickHouse arrays combine neatly with GROUP BY aggregation. We show how arrays track sequences and offer a couple of ways to do funnel analysis.
ClickHouse contributors regularly add analytic features that go beyond standard SQL. This design approach is common in successful open source projects and reflects a bias toward solving real-world problems creatively. Arrays are a great example.
Mutable data is generally unwelcome in OLAP databases. ClickHouse is no exception to the rule. Like some other OLAP products, ClickHouse did not even support updates originally. Later on, updates were added, but like many other things they were added…
A common use case in time series applications is to get the measurement value at a given point of time. For example, if there is a stream of measurements, one often needs to query the measurement as of current time…
Jan 1, 2020Cost-efficiency and performance are critical for big data analytics. For this reason a recent blog post from ScyllaDB guys caught our attention. They collected over 500 billion data points and were able to query it with 1B rows/sec…
July 10, 2019Modern analytical databases would not exist without efficient data compression. Storage gets cheaper and more performant, but data sizes typically grow even faster. Moore’s Law for big data outperforms its analogy in hardware. In our blog we already…
May 23, 2019ClickHouse offers incredible flexibility to solve almost any business problem in a multiple of ways. Schema design plays a major role in this. For our recent benchmarking using the Time Series Benchmark Suite (TSBS) we replicated TimescaleDB schema…
In our previous articles we demonstrated that ClickHouse — a general purpose analytics DB — can easily compete with specialized DBMSs for time series data: TimescaleDB and InfluxDB. There were, however, certain queries, pretty typical for time series, where ClickHouse…
Dec 4, 2018Our previous take on time series benchmarks attracted a lot of interest so we decided to dig into more details. We conducted 3 different ClickHouse scalability tests using the same TSBS dataset and benchmarking infrastructure. In this article…
Nov 15, 2018Once upon a time we spotted TSBS (https://github.com/timescale/tsbs) — Time Series Benchmark Suite, started by InfluxDB engineers and polished to perfection by TimescaleDB team. The suite allows to compare apples-to-apples when testing different databases: it is a framework…
