ClickHouse vs. OpenText Vertica

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

Vertica as a data warehouse to deliver analytics in-house and even to your client base on scale is not rivaled anywhere in the market. Frankly, in my experience it is not even close to equaled. Because it is such a powerful data warehouse, some people attempt to use it as a transactional database. It certainly is not one of those. Individual row inserts are slow and do not perform well. Deletes are a whole other story. RDBMS it is definitely not. OLAP it rocks.

Incentivized

• Opensource
• High performance
• Multiple engines to adapt user cases
• Easy configuration of data replication

Incentivized

• Extremely fast query performance - Vertica is one of the fastest query engines out there.
• Scales to TBs - Scales reasonably well up to 10-20 nodes and 10 - 100s of TB of data.
• Easy to Use - Fairly easy to user, we made quite some headway with just 1 person running it for a while.

Incentivized

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

Incentivized

• Could use some work on better integrating with cloud providers and open source technologies. For AWS you will find an AMI in the marketplace and recently a connector for loading data from S3 directly was created. With last release, integration with Kafka was added that can help.
• Managing large workloads (concurrent queries) is a bit challenging.
• Having a way to provide an estimate on the duration for currently executing queries / etc. can be helpful. Vertica provides some counters for the query execution engine that are helpful but some may find confusing.
• Unloading data over JDBC is very slow. We've had to come up with alternatives based on vsql, etc. Not a very clean, official on how to unload data.

Incentivized

I haven't had any recent opportunity to reach out to Vertica support. From what I remember, I believe whenever I reached out to them the experience was smooth.

Incentivized

ClickHouse was not compared to them as a competitor but as the ideal partner to complete an information analysis system, providing users with the most complete and efficient tools. Therefore, in this case it was considered that it would be the ideal candidate due to its characteristics compared to the other competitors.

Incentivized

Vertica performs well when the query has good stats and is tuned well. Options for GUI clients are ugly and outdated. IO optimized: it's a columnar store with no indexing structures to maintain like traditional databases. The indexing is achieved by storing the data sorted on disk, which itself is run transparently as a background process.

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

• Positive impact on ROI by being able to get customer insights in real-time.
• Positive ROI through reduced time to set-up and maintain Vertica instances.

Incentivized