I will be presenting at the ClickHouse MySQL Silicon Valley Meetup on Wednesday, October 25, 2017, at 6:30 PM.

ClickHouse is a real-time analytical database system. Even though they’re only celebrating one year as open source software, it has already proved itself ready for the serious workloads. We will talk about ClickHouse in general, some internals and why it is so fast. ClickHouse works in conjunction with MySQL – traditionally weak for analytical workloads – and this presentation demonstrates how to make the two systems work together.

My talk will cover how we can improve the experience with real-time analytics using ClickHouse, and how we can …

In this blog, I’ll use ClickHouse and Tabix to look at a new very large dataset for research.

It is hard to come across interesting datasets, especially a big one (and by big I mean one billion rows or more). Before, I’ve used on-time airline performance available from BUREAU OF TRANSPORTATION STATISTICS. Another recent example is NYC Taxi and Uber Trips data, with over one billion records.

However, today I wanted to mention an interesting dataset I found recently that has been available since 2015. This is Reddit’s comments and submissions dataset, made possible thanks to Reddit’s generous API. The …

Join Percona’s CTO Vadim Tkachenko @VadimTk and Altinity’s Co-Founder, Alexander Zaitsev as they present Supercharge Your Analytics with ClickHouse on Thursday, September 14, 2017, at 10:00 am PDT / 1:00 pm EDT (UTC-7).

Reserve Your Spot

ClickHouse is a real-time analytical database system. Even though they’re only celebrating one year as open source software, it has already proved itself ready for serious …

In this blog post, we’ll look at nested data structures in ClickHouse and how this can be used with PMM to look at queries.

Nested structures are not common in Relational Database Management Systems. Usually, it’s just flat tables. Sometimes it would be convenient to store unstructured information in structured databases.

We are working to adapt ClickHouse as a long term storage for Percona Monitoring and Management (PMM), and particularly to store detailed information about queries. One of the problems we are trying to solve is to count the different errors that cause a particular query to fail.

For example, for date 2017-08-17 the query:

"SELECT foo FROM bar WHERE …

In this blog, we’ll look at ClickHouse on its one year anniversary.

It’s been a year already since the Yandex team released ClickHouse as open source software. I’ve had an interest in this project from the very start, as I didn’t think there was an open source analytical database that could compete with industry leaders like Vertica (for example).

This was an exciting year for ClickHouse early adopters. Let’s look at what it accomplished so far.

ClickHouse initially generated interest due to the Yandex name – the most popular search engine in Russia. It wasn’t long before jaw-dropping responses popped up: guys, this thing is crazy fast! Many early adopters who tried ClickHouse were really impressed.

Fast doesn’t mean convenient …

“Spark and Ignite can complement each other very well. Ignite can provide shared storage for Spark so state can be passed from one Spark application or job to another. Ignite can also be used to provide distributed SQL with indexing that accelerates Spark SQL by up to 1,000x.”–Nikita Ivanov.

I have interviewed Nikita Ivanov,CTO of GridGain.
Main topics of the interview are Apache Ignite, Apache Spark and MySQL, and how well they perform on big data analytics.

RVZ

Q1. What are the main technical challenges of SaaS development projects?

Nikita Ivanov: SaaS requires that the applications be highly responsive, reliable and web-scale. SaaS development projects face many of the same challenges as …

In this blog post, we’ll look at how ClickHouse performs in a general analytical workload using the star schema benchmark test.

We have mentioned ClickHouse in some recent posts (ClickHouse: New Open Source Columnar Database, Column Store Database Benchmarks: MariaDB ColumnStore vs. Clickhouse vs. Apache Spark), where it showed excellent results. ClickHouse by itself seems to be event-oriented RDBMS, as its name suggests (clicks). Its primary purpose, using Yandex Metrica (the system similar to Google Analytics), also points to an event-based nature. We also can see there is …

This blog shares some column store database benchmark results, and compares the query performance of MariaDB ColumnStore v. 1.0.7 (based on InfiniDB), Clickhouse and Apache Spark.

I’ve already written about ClickHouse (Column Store database).

The purpose of the benchmark is to see how these three solutions work on a single big server, with many CPU cores and large amounts of RAM. Both systems are massively parallel (MPP) database systems, so they should use many cores for SELECT queries.

For the benchmarks, I chose …