We performed a comparison between BigQuery and Vertica based on real PeerSpot user reviews.
Find out in this report how the two Cloud Data Warehouse solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The query tool is scalable and allows for petabytes of data."
"The solution's reporting, dashboard, and out-of-the-box capabilities match exactly our requirements."
"It has a proprietary way of storing and accessing data in its own data store and is 100% managed without you needing to install anything. There is no need to arrange for any infrastructure to be able to use this solution."
"BigQuery can be used for any type of company. It has the capability of building applications and storing data. It can be used for OLTP or OLAP. It has many other products within the Google space."
"There are some performance features like partitioning, which you can do based on an integer, and it improves the performance a lot."
"Even non-coders can review the data in BigQuery."
"The most valuable features of this solution, in my opinion, are speed and performance, as well as cost-effectiveness."
"BigQuery excels at structuring data, performing predictions, and conducting insightful analyses and it leverages machine learning and artificial intelligence capabilities, powered by Google's Duarte AI."
"Vertica is a columnar database, this support our developments in analytics, advanced analytics, and ETL process with large sets of data."
"I enjoy the cybersecurity and backup features."
"Vertica enabled us to close large deals. Customers with large data sets had to be migrated from PostgreSQL to Vertica due to performance."
"The performance is very good and the aggregate records are fast."
"For me, It's performance, scalability, low cost, and it's integrated into enterprise and big data environments."
"The hardware usage and speed has been the most valuable feature of this solution. It is very fast and has saved us a lot of money."
"Vertica gives knowledgeable users and DBAs excellent tools for tuning."
"Its projections and encoding are excellent tools for tuning large volumes."
"We'd like to have more integrations with other technologies."
"The processing capability can be an area of improvement."
"The main challenges are in the areas of performance and cost optimizations."
"With other columnar databases like Snowflake, you can actually increase your VM size or increase your machine size, and you can buy more memory and it will start working faster, but that's not available in BigQuery. You have to actually open a ticket and then follow it up with Google support."
"As a product, BigQuery still requires a lot of maturity to accommodate other use cases and to be widely acceptable across other organizations."
"They could enhance the platform's user accessibility."
"The price could be better. Compared to competing solutions, BigQuery is expensive. It's only suitable for enterprise customers, not small and medium-sized businesses, as they cannot afford this kind of solution. In the next release, it would be better if they improved their AI bot. Although machine learning and artificial intelligence are doing wonders, there is still a lot of room to enhance them."
"Some of the queries are complex and difficult to understand."
"Monitoring tools need to be lightweight. They should not take up heavy resources of the main server."
"Limitations in group by projections is where I would like to see an improvement."
"They could improve on customer service."
"Some of our small to medium-sized customers would like to see containerization and flexibility from the deployment standpoint."
"One feature, which has really benefited us, is the scalability offered by Vertica as it has enabled Pythian's clients to manage data with agility."
"In a future release, we would like to have artificial intelligence capabilities like neural networks. Customers are demanding this type of analytics."
"They could improve the integration and some of the features in the cloud version."
"I believe the installation process could be streamlined."
BigQuery is ranked 5th in Cloud Data Warehouse with 31 reviews while Vertica is ranked 7th in Cloud Data Warehouse with 83 reviews. BigQuery is rated 8.2, while Vertica is rated 8.2. The top reviewer of BigQuery writes "Expandable and easy to set up but needs more local data residency". On the other hand, the top reviewer of Vertica writes " A user-friendly tool that needs to improve its documentation part". BigQuery is most compared with Snowflake, Teradata, Oracle Autonomous Data Warehouse, Apache Hadoop and AWS Lake Formation, whereas Vertica is most compared with Snowflake, SQL Server, Amazon Redshift, Teradata and Oracle Database. See our BigQuery vs. Vertica report.
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