ClickHouse vs. Presto

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
ClickHouse
Score 9.1 out of 10
N/A
ClickHouse is an open-source, column-oriented OLAP database system enabling real-time analytical reports using SQL queries. With linear scalability, it handles trillions of rows and petabytes of data. ClickHouse Cloud offers a scalable serverless solution for real-time analytics.N/A
Presto
Score 2.6 out of 10
N/A
Presto is an open source SQL query engine designed to run queries on data stored in Hadoop or in traditional databases. Teradata supported development of Presto followed the acquisition of Hadapt and Revelytix.N/A
Pricing
ClickHousePresto
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
ClickHousePresto
Free Trial
YesNo
Free/Freemium Version
YesNo
Premium Consulting/Integration Services
YesNo
Entry-level Setup FeeOptionalNo setup fee
Additional DetailsPay for what is used: It automatically scales up and down compute resources based on the user's workload It scales storage and compute separately It automatically scales unused resources down to zero so that users don’t pay for idle services
More Pricing Information
Best Alternatives
ClickHousePresto
Small Businesses
SingleStore
SingleStore
Score 8.9 out of 10
SingleStore
SingleStore
Score 8.9 out of 10
Medium-sized Companies
Snowflake
Snowflake
Score 8.9 out of 10
Snowflake
Snowflake
Score 8.9 out of 10
Enterprises
SAP IQ
SAP IQ
Score 9.0 out of 10
SAP IQ
SAP IQ
Score 9.0 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
ClickHousePresto
Likelihood to Recommend
10.0
(2 ratings)
7.8
(2 ratings)
User Testimonials
ClickHousePresto
Likelihood to Recommend
ClickHouse, Inc.
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.
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Open Source
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
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Pros
ClickHouse, Inc.
  • 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
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Open Source
  • 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.
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Cons
ClickHouse, Inc.
  • Avro data manipulation
  • Kafka consistency
  • DDL operations errors (by replica configuration)
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Open Source
  • 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.
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Alternatives Considered
ClickHouse, Inc.
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.
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Open Source
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.
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Return on Investment
ClickHouse, Inc.
  • 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
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Open Source
  • 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.
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