ClickHouse vs. Percona Server for MySQL vs. Presto

The most important thing when using ClickHouse is to be clear that the scenarios in which you want to use it really are the right ones. Many users think that when a database is very fast for a specific use case, it can be extrapolated to other contexts (most of the time different) in which a previous analysis has not been carried out.

ClickHouse is an analytical database, as such, it should be used for such purposes, where the information is stored correctly, the data volumes are really large and the queries to be performed are not the typical traditional queries on several columns with multiple aggregations. ClickHouse is not the solution for this.

On the other hand, if your case is not one of the above, it is quite possible that ClickHouse can help you. Where ClickHouse shines is when you are looking for aggregation over a particular column in large volumes of data.

Incentivized

Percona Server for MySQL covers 100% of our requirements in terms of our OLTP traffic and provides the High Availability levels required through a typical primary and 2 replica's using semi-synchronous replication. We're able to scale our writes using sharding, but a true distributed database would be a great option on top of this. In terms of OLAP traffic, we leverage columns stores available, but Percona Server fairs well

Presto is for interactive simple queries, where Hive is for reliable processing. If you have a fact-dim join, presto is great..however for fact-fact joins presto is not the solution.. Presto is a great replacement for proprietary technology like Vertica

Incentivized

• Their MergeTree table engine provide impressive performance for data insert in bulk
• Not only data insert but also the way MergeTree engine uses Primary Keys to sort the data and perform data skipping based on the granules its also their secret for ridiculous fast queries
• Data compression its also great
• They provide especial table engines that allow you to read data directly from other sources like S3
• Since its written with C++ you have very granular data types and especial ones like enum, LowCardinality and etc, they save you a lot of storage since are stored as integer values
• ClickHouse functions besides the ones that respect ANSI Standards are also awesome and useful

Incentivized

• Faster than other server solutions
• Installation and configuration process is easy from the user's standpoint
• Easy to learn and good support

Incentivized

• Linking, embedding links and adding images is easy enough.
• Once you have become familiar with the interface, Presto becomes very quick & easy to use (but, you have to practice & repeat to know what you are doing - it is not as intuitive as one would hope).
• Organizing & design is fairly simple with click & drag parameters.

Incentivized

• Avro data manipulation
• Kafka consistency
• DDL operations errors (by replica configuration)

Incentivized

• Better documentation
• A better UI

• Presto was not designed for large fact fact joins. This is by design as presto does not leverage disk and used memory for processing which in turn makes it fast.. However, this is a tradeoff..in an ideal world, people would like to use one system for all their use cases, and presto should get exhaustive by solving this problem.
• Resource allocation is not similar to YARN and presto has a priority queue based query resource allocation..so a query that takes long takes longer...this might be alleviated by giving some more control back to the user to define priority/override.
• UDF Support is not available in presto. You will have to write your own functions..while this is good for performance, it comes at a huge overhead of building exclusively for presto and not being interoperable with other systems like Hive, SparkSQL etc.

Incentivized

It is easy to install and use. Using it along with Percona Monitoring and Management makes it even easier to use.

Incentivized

We are using opensource so we have not used customer support.

ClickHouse outperforms, especially in costs, since its compression/indexing engines are so smart, and even with very low computing power, you can already perform huge analyses of the data.

Incentivized

Performance and stability sets Percona Server for MySQL apart from the rest. Percona embraces the upstream version and contributes towards the upstream version making MySQL stronger on two fronts and thus having a much larger community. Many quality contributions have been made by Percona into the base code. Percona provides great tools to support Percona Server for MySQL and this makes the monitoring and management easier

Presto is good for a templated design appeal. You cannot be too creative via this interface - but, the layout and options make the finalized visual product appealing to customers. The other design products I use are for different purposes and not really comparable to Presto.

Incentivized

• Queries that used to take more than 2 minutes now take less than 1 second
• Possibility to analyze use cases in real time (before was impossible)
• The applications are more complete and the users decisions are better

Incentivized

• At the performance level, it maintains and even improves other open-source databases such as MariaDB or some commercial ones such as Oracle.
• If we compare it with MySQL, we could have up to 50% improvement in performance.
• For some small companies or startups, the price of the complete solution and the support can be a bit high.

Incentivized

• Presto has helped scale Uber's interactive data needs. We have migrated a lot out of proprietary tech like Vertica.
• Presto has helped build data driven applications on its stack than maintain a separate online/offline stack.
• Presto has helped us build data exploration tools by leveraging it's power of interactive and is immensely valuable for data scientists.

Incentivized