In this research,  I wanted to see what kind of performance improvements could be gained by using a ClickHouse data source rather than PostgreSQL. Assuming that I would see performance advantages with using ClickHouse, would those advantages be retained if I access ClickHouse from within postgres using a foreign data wrapper (FDW)? The FDW in question is clickhousedb_fdw – an open source project from Percona!

The database environments under scrutiny are PostgreSQL v11, clickhousedb_fdw and a ClickHouse database. Ultimately, from within PostgreSQL v11, we are going to issue various SQL queries routed through our clickhousedb_fdw to the ClickHouse database. Then we’ll see how the FDW performance compares with those same queries executed in native PostgreSQL and native ClickHouse.

Clickhouse Database

ClickHouse is an open source column based database management system which can achieve performance of between 100 and …

This year at our Open Source Database Conference we’re celebrating open source database technologies that don’t fit into the MySQL®, MongoDB®, MariaDB®, or PostgreSQL realms by featuring them in their very own track. The glamorously-named Other Open Source Databases track! As unbiased champions of open source database solutions, we embrace all flavors of open source database, and pride ourselves at presenting one of the biggest events dedicated to any and all OSDBs.

Another innovation this year is the introduction of a Java programming for open source databases track. Maybe that would be of interest?

The conference takes place at the end of May in Austin, a fantastic place to visit, and state capital of Texas.

As mentioned in …

Following my post from a year ago https://www.percona.com/blog/2017/07/06/clickhouse-one-year/, I wanted to review what happened in ClickHouse during this year.
There is indeed some interesting news to share.

1. ClickHouse in DB-Engines Ranking. It did not quite get into the top 100, but the gain from position 174 to 106 is still impressive. Its DB-Engines Ranking score tripled from 0.54 last September to 1.57 this September

And indeed, in my conversation with customers and partners, the narrative has changed from: “ClickHouse, what is …

Join Percona Chief Evangelist Colin Charles as he covers happenings, gives pointers and provides musings on the open source database community.

OSCON happened last week and was incredible. It is true there was less of a database focus, and a lot more topics covered. In fact, you’d have found it hard to find database content. There was plenty of interesting content around AI/ML, cloud, SRE, blockchain and more. As a speaker, the 40-minute sessions that included a Q and A session was quite compact (I felt it was a little too short, and many speakers sped up towards the end). I guess it will make for more blog content.

The conference’s open source ethos is still extremely strong, and the keynotes exemplified that. It was not just the 20th anniversary of OSCON, but also the 20th anniversary of the …

Join Percona CTO Vadim Tkachenko at the Cloud Native Utah meetup in Salt Lake City on Tuesday, May 8, 2018, for an Intro to ClickHouse.

Next week, I’ll be switching from MyRocks performance testing and present an introduction to ClickHouse to the Cloud Native Utah meetup.

Interestingly enough, even though it is totally different from OLTP engines, ClickHouse uses a MergeTree engine. MergeTree engines have a lot of similarities with Log Structured Merge Tree (which is what is used by MyRocks / RocksDB). This the structure is optimized to run on huge datasets / low memory scenarios.

PingCAP TiDB and …

In this blog post, I’ll look at how you can analyze MySQL audit logs (Percona Server for MySQL) with ClickHouse and ClickTail.

Audit logs are available with a free plugin for Percona Server for MySQL (https://www.percona.com/doc/percona-server/LATEST/management/audit_log_plugin.html). Besides providing insights about activity on your server, you might need the logs for compliance purposes.

However, on an active server, the logs can get very large. Under a sysbench-tpcc workload, for …

In this blog post, I’ll look at how you can analyze raw MySQL query logs with ClickHouse.

For typical query performance analyses, we have an excellent tool in Percona Monitoring and Management. You may want to go deeper, though. You might be longing for the ability to query raw MySQL “slow” query logs with SQL.

There are a number of tools to load the MySQL slow query logs to a variety of data stores. For example, you can find posts showing how to do it with LogStash. While very flexible, these solutions always look too complicated and limited in functionality to me.   

By far the best solution to parse and load MySQL slow query logs (among multiple log types supported) is Charity …

In this blog post, I will talk about archiving MySQL tables in ClickHouse for storage and analytics.

Why Archive?

Hard drives are cheap nowadays, but storing lots of data in MySQL is not practical and can cause all sorts of performance bottlenecks. To name just a few issues:

1. The larger the table and index, the slower the performance of all operations (both writes and reads)
2. Backup and restore for terabytes of data is more challenging, and if we need to have redundancy (replication slave, clustering, etc.) we will have to store all the data N times

The answer is archiving old data. Archiving does not necessarily mean that the data will be permanently removed. Instead, the archived data can be placed into long-term storage (i.e., AWS S3) or loaded into a …

In this post, we’ll look at updating and deleting rows with ClickHouse. It’s the second of two parts.

In the first part of this post, we described the high-level overview of implementing incremental refresh on a ClickHouse table as an alternative support for UPDATE/DELETE. In this part, we will show you the actual steps and sample code.

Prepare Changelog Table

First, we create the changelog table below. This can be stored on any other MySQL instance separate from the source of our analytics table. When we run the change capture script, it will record the data on this table that we can consume later with the incremental refresh script:

CREATE TABLE `clickhouse_changelog` (
  `db` varchar(255) NOT NULL …

In this post, we’ll look at updating and deleting rows with ClickHouse. It’s the first of two parts.

Update: Part 2 of this post is here.

ClickHouse is fast – blazing fast! It’s quite easy to pick up, and with ProxySQL integrating with existing applications already using MySQL, it’s way less complex than using other analytics options. However, ClickHouse does not support UPDATE/DELETE (yet). That entry barrier can easily dissuade potential users despite the good things I mentioned.

If there is a will, there is a way! We have so far taken advantage of the new feature that supports more granular partitioning strategy (by week, by day or something else). With more …