--- title: Rocket Vertica Reviews meta_title: 'Rocket Vertica Reviews 2026: Details, Pricing, & Features | G2' meta_description: Filter 216 reviews by the users' company size, role or industry to find out how Rocket Vertica works for a business like yours. aggregate_rating: rating_value: 4.3 review_count: 216 scale: '5' date_modified: '2026-08-07' parent_category: name: IT Infrastructure url: https://www.g2.com/categories/it-infrastructure --- # Rocket Vertica Reviews **Vendor:** Rocket Software **Category:** [Data Warehouse Solutions](https://www.g2.com/categories/data-warehouse) **Average Rating:** 4.3/5.0 **Total Reviews:** 216 ## About Rocket Vertica Vertica is the unified analytics platform, based on a massively scalable architecture with a broad set of analytical functions spanning event and time series, pattern matching, geospatial, and built-in machine learning capability. Vertica enables data analytics teams to easily apply these powerful functions to large and demanding analytical workloads, arming them and their customers with predictive business insights. Vertica provides a unified analytics platform across major public clouds and on-premises data centers, and integrates data in cloud object storage and HDFS without forcing any data movement. Available as a SaaS option, or as a customer-managed platform, Vertica helps teams combine growing data siloes for a more complete view of available data. Vertica features separation of compute and storage, so teams can spin up storage and compute resources as needed, then spin down afterwards to reduce costs. ## Rocket Vertica Reviews ### 1. Best columnar database in the market **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Airlines/Aviation | Enterprise (> 1000 emp.) **Reviewed Date:** March 06, 2019 **What do you like best about Rocket Vertica?** I haven't seen any other database in the marketplace that can beat the performance of Vertica **What do you dislike about Rocket Vertica?** Currently it takes a lots of time to re balance the cluster, when you add or remove a node. **Recommendations to others considering Rocket Vertica:** If you are looking for more scalable version, then use EON mode. **What problems is Rocket Vertica solving and how is that benefiting you?** Big data analytics; That results in better customer satisfaction. ### 2. Hybrid Storage Options are making Vertica more versatile **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Enterprise (> 1000 emp.) **Reviewed Date:** March 09, 2019 **What do you like best about Rocket Vertica?** Recently added features - Complex Data types, Delegation Tokens, Hierarchial Partitions, Upcoming features New Storage options - EON on Prem, EON on GCP, Enterprise on GCP libhdfs+ erasure coding support, DBD lite, Parquet enhancements **What do you dislike about Rocket Vertica?** Copy cluster not possible across heterogeneous clusters **What problems is Rocket Vertica solving and how is that benefiting you?** OLAP analysis and reporting ### 3. Vertica in a League of its Own **Rating:** 5.0/5.0 stars **Reviewed by:** Cameron W. | Information Technology Logistics , Computer Software, Enterprise (> 1000 emp.) **Reviewed Date:** May 04, 2018 **What do you like best about Rocket Vertica?** Vertica query optimizer relies on up-to-date statistics for tables, schema, and the database. The statistics allow the optimizer to determine the most efficient plan to execute a query **What do you dislike about Rocket Vertica?** I am not able to change Profile data, Its saved in the pre made tables provided by creator. **Recommendations to others considering Rocket Vertica:** Quires can be made in any fashion as you need SQL Functions, Each function is annotated with behavior type as immutable, stable or volatile. **What problems is Rocket Vertica solving and how is that benefiting you?** We are able to store more data, And customize that data into what we need. ### 4. Vertica is immensely useful for structured data **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Internet | Enterprise (> 1000 emp.) **Reviewed Date:** July 30, 2018 **What do you like best about Rocket Vertica?** High amount of uptime Clear documentation Great python modules **What do you dislike about Rocket Vertica?** I have no complaints about Vertica, but I do slightly prefer mysql due to syntax preferences **What problems is Rocket Vertica solving and how is that benefiting you?** Data analystics ### 5. Great product **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Hospital & Health Care | Mid-Market (51-1000 emp.) **Reviewed Date:** July 14, 2017 **What do you like best about Rocket Vertica?** HPE is one of the few solutions in their space that actually care about making an effective solution for their customers. Most companies just want the flashy new buzz words, but HPE prioritizes the real needs of their customers. **What do you dislike about Rocket Vertica?** There were no particular things I disliked **What problems is Rocket Vertica solving and how is that benefiting you?** Moved from Oracle to HPE Vertica, saved massive amounts of money on infrastructure and allowed us to scale. ### 6. Incredible **Rating:** 5.0/5.0 stars **Reviewed by:** Marcello P. | Business Intelligence Analyst, Computer Software, Small-Business (50 or fewer emp.) **Reviewed Date:** February 15, 2016 **What do you like best about Rocket Vertica?** Before I met HP Vertica, I've worked with a few other column-store databases. Few were easy to install and use, but were not reliable; others had good performance and stability but were definitely not use to deploy. After 2-3 hours of deciding to try Vertica, I was running queries on it. So what I like the best: - Easy to deploy; - Easy to Configure; - Plenty of native tools to help the maintenance; - Plenty of *clear* documentation to help you though; - Fast - hands-down, the fastest for hardware I've worked with; - Small - incredible compression rates to the data; - Reliable/Stable fault-tolerant and - in my case - no data loss issues; - No need for planning, analyzing or maintaining table indexes; - Familiar way of loading data [PostgreSQL-like / COPY] **What do you dislike about Rocket Vertica?** Even though most of the problems I've had were already answered in public forums from the Vertica Communiy - I use the community version -, I feel like there's not a big crowd trying to help or at least trying to make their voice heard online. **Recommendations to others considering Rocket Vertica:** Read all the documents you can about Hardware Requirements. Even though it looks big, it's a very complete document, every DBA should beware of. Because Vertica looks from outside a lot like PostgreSQL, users tend to forget some of its specificities when writing SQL queries or doing some other maintenance tasks. So beware of subqueries, data types, row-inserts - prefer bulk inserts - table/column drops, etc. **What problems is Rocket Vertica solving and how is that benefiting you?** Using the Vertica Community Version, we were able to increase - sometimes by a factor of 10 - the speed of Data Warehouses queries. As we didn't have much time to try tens of different databases, Vertica showed handy when it comes to Install/Loading data. ### 7. Fast and powerful analytics platform **Rating:** 5.0/5.0 stars **Reviewed by:** Traian A. | Big Data Technical Director, Computer Software, Small-Business (50 or fewer emp.) **Reviewed Date:** April 14, 2015 **What do you like best about Rocket Vertica?** A lightweight performance-focused implementation and various features: − IO optimized - it's a columnar store, 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; − Reduced data storage footprint through advanced encoding schemas (RLE, common-delta, etc.) as well as compression algorithms Ability to operate directly on the encoded data; − Querying will only read specific columns' data, pushing predicates to the storage layer is very important, analytical queries on row store databases will never be able to match that. Columns with RLE are similar to having an infinite number of partitions and also sub-partitioning levels, in some cases if multiple predicates are used with proper sorts it can be incredibly fast. ANSI SQL compliant, SQL-92 and most of the SQL-99 standard; easy to extend with user-defined functions written in C++, Java, R and to turn it into a powerful data processing engine that is able to easily parallelize, distribute, and partition datasets for processing (moving processing between Hadoop Pig/Hive and Vertica is very simple). Developer friendly: from verbose explain plans and query profiles to the ability to track execution engine metrics by query paths/operators (e.g. CPU cycles used, rows processed, bytes sent over network, etc.) Easy to setup and manage fairly large clusters. In our experience a dba should be able to handle many large clusters. Very stable, easy to scale, reliable, highly available (most of issues we had were hardware issues; never had down time or lost any data). Constant addition of features, improvements (e.g. support for large data types, GIS package, flex tables, etc.). **What do you dislike about Rocket Vertica?** Price may be high; small startups trying to keep costs down may choose open source (e.g. HBase, etc.) There were some stability issues at first when certain errors were bringing down nodes, etc. but have been solved for a while Supporting large workloads (many concurrent queries) is still not a strength of Vertica. Loading very large data sets may use some improvements (e.g. in some cases you may have more capacity to parse and segment the data on the client side and stream the data to a specific node thereby directly reducing load and data redistribution between nodes. Depending on the data model used, in some cases you might have trouble optimizing the queries (large joins with large group-by's on columns across multiple relations); **Recommendations to others considering Rocket Vertica:** Dr. Michael Stonebraker was the co-founder and architect (Vertica is based on the C-Store project). If you haven't heard of him it suffices to know that he received the 2015 Turing Award for his contributions to database systems. You will need to understand its physical layer and how your queries will access and process the data to come up with the right design (Database Designer can be a great help to get you started) and then you will be amazed how fast you can do data filtering, joins and group bys, etc. on billions of records with a handful of nodes in minutes. At the same time if your queries are suffering from bad segmentation, can't do block processing, push predicates to storage layer, etc. then you will not really get anything from what Vertica has to offer. At the same time, using Vertica as a traditional OLTP database, with many small transactions inserting/deleting/updating data is not going to take you very far so that’s an obvious case where Vertica is not recommended. With all the NoSQL, NewSQL buzz I’ve seen there is a misconception that SQL is old, RDBMS don't scale, etc. but the reality is many of these NoSQL products are adding more and more SQL-like features to stay competitive so be sure SQL is here to stay. **What problems is Rocket Vertica solving and how is that benefiting you?** Vertica is not the silver bullet but based on my experience in 9/10 cases in which you need an analytical database, Vertica is probably the answer. Currently we're using Vertica more as a data processing engine in conjunction with a Hadoop cluster as some of the steps are way more efficient than doing them in Hadoop and easier to manage (e.g. iterative processing steps). We also had a pretty good experience using it with Storm and Hadoop. The main reasons I usually choose Vertica are it's the performance that’s fairly easy to scale and extend. ### 8. Vertica as a Lightening Fast BI Data Source **Rating:** 5.0/5.0 stars **Reviewed by:** David L. P. | Lead Database Engineer / Business Intelligence Architect, Information Technology and Services, Mid-Market (51-1000 emp.) **Reviewed Date:** April 17, 2015 **What do you like best about Rocket Vertica?** Vertica is truly the fastest column-store database implementation on the market today. **What do you dislike about Rocket Vertica?** There are still some glitches in the bulk import COPY process that requires inlining the source query details and the management tool ecosystem is still in the process of maturing. **Recommendations to others considering Rocket Vertica:** Clearly understand your requirements prior to implementing a column-store database. Queries with complex WHERE clauses and large scale aggregation can complete with lightening speed, new data can be INSERTed with very fast caching, but rapid UPDATEs and DELETEs will need special design considerations (such as chunking, reordering, and/or tombstoning) in a high velocity solution. **What problems is Rocket Vertica solving and how is that benefiting you?** Vertica's column-store solution essentially makes every column its own index -- while still facilitating row-level selection of data. This makes previously unfeasible requirements -- such as "filter on every column" -- possible even with interactive user interfaces. ### 9. Fantastic Analytics Platform **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Hospital & Health Care | Small-Business (50 or fewer emp.) **Reviewed Date:** April 13, 2015 **What do you like best about Rocket Vertica?** Very fast and relatively easy to implement. Very nice SQL implementation (albeit with some minor limitations) with great bulk load facilities. I successfully migrated multiple multi-terabyte customer databases from Netezza to Vertica with huge increases in performance, lower TCO, and reduced administrative overhead. **What do you dislike about Rocket Vertica?** Refreshing lower environments with data from upper environments is easy if the clusters have the same number of nodes, otherwise you have to get more creative. There are out-of-the-box methods to facilitate data refreshes between differing cluster sizes, but it's more of a roll-your-own approach. Backup and recovery faces the same challenge in that recovering to like cluster sizes is possible, but not so with a target cluster of a different size. Vertica's SQL implementation is really good, however, there are a number of odd and/or limited implementations for certain things (e.g. NOT IN with NULL returned by subqueries, CTE support but not recursive CTE support, etc). This may be addressed in the latest versions, but these items were present in 7.0.x. The operating system-level configuration is fairly straightforward, however Vertica is very sensitive to even the slightest misconfiguration. Highly recommend that implementers follow the vendor documentation to the letter when configuring host servers. Also recommend a high performance, direct-attached storage device for performant backups. **Recommendations to others considering Rocket Vertica:** Purchase dedicated, direct-attached storage devices for backups (1 per environment), follow vendor configuration instructions to the letter, send your DBA to training, and study up on the SQL limitations. **What problems is Rocket Vertica solving and how is that benefiting you?** Legacy DW appliance replacement with lower TCO and improved performance with lots of room to scale. ### 10. Used for batch logs analysis **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Computer Software | Small-Business (50 or fewer emp.) **Reviewed Date:** April 29, 2015 **What do you like best about Rocket Vertica?** It presents a relational DB feel but works under the hood as a columnar store. We achieved two orders-of-magnitude over several other tools and eliminated the need for pivot tables entirely. The polish and easy of setup also played a big factor in getting me to use it, even though I generally favor open-source solutions for holding data. **What do you dislike about Rocket Vertica?** It's not open-source. I prefer to store data long-term in open-source solutions to avoid lock-in. **Recommendations to others considering Rocket Vertica:** If you can afford it, use it. Or if you can keep your internal DB lower than 1TB use that. **What problems is Rocket Vertica solving and how is that benefiting you?** It was fast enough to build a dashboard on top of while facilitating many huge simultaneous queries without need for pivot tables. It saved us huge amount of man hours as we didn't have to maintain partial queries in tables for represent different views on data. ### 11. Vertica , and its Stability **Rating:** 4.5/5.0 stars **Reviewed by:** Matthew S. | MySQL DBA, Computer Games, Enterprise (> 1000 emp.) **Reviewed Date:** April 20, 2015 **What do you like best about Rocket Vertica?** At my company, we use vertica for data that has to ensure 100% uptime, such as payments, and other monetary processing. Since there is major redundancy, unless a major datacenter outage, vertica is very stable and rarely goes down fully. **What do you dislike about Rocket Vertica?** I dislike the UI. I find it clunky and tends to be anti cognitive. **Recommendations to others considering Rocket Vertica:** Better UI **What problems is Rocket Vertica solving and how is that benefiting you?** We use it for the mobile monetary processing. It has been amazing, and works clean. ### 12. Vertica: A fast and cost effective database for handling Big Data **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Higher Education | Enterprise (> 1000 emp.) **Reviewed Date:** April 20, 2015 **What do you like best about Rocket Vertica?** It is fast and I have been told it is easy to install. Adding and removing nodes is also very painless. It's a RDBMS which can scale easily. User Defined Functions can be written to bring additional functionality. It can also be integrated with Hadoop and the data can be used to run MapReduce jobs. **What do you dislike about Rocket Vertica?** It's not open source and is owned by HP. So it's a paid distribution and its future is dependent on HP. **Recommendations to others considering Rocket Vertica:** I would recommend you check Hive before you jump to this. I have been told that it has made good progress in the past few years. **What problems is Rocket Vertica solving and how is that benefiting you?** We wanted a database for handling Big Data. We started with Hive but it converted its queries to multiple MapReduce jobs. In Hadoop, after each subsequent MapReduce job, data is written to disk. This slows down the queries by a large margin. ### 13. Great performance **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Computer Networking | Mid-Market (51-1000 emp.) **Reviewed Date:** April 07, 2015 **What do you like best about Rocket Vertica?** The ability to use projections to optimize the performance of multiple types of queries on the same data. Live aggregates have also been useful in increasing the efficiency of our database. **What do you dislike about Rocket Vertica?** Getting educated is harder than it should be. My company had a trainer come in, but it would have been nice if there were more self-paced materials. **What problems is Rocket Vertica solving and how is that benefiting you?** In terms of query performance, we went from minutes down to sub-second timing. This enabled us to deliver data in new ways, and we have completely changed how our users experience our products. ### 14. Efficient Data Ware House for Reporting **Rating:** 3.5/5.0 stars **Reviewed by:** Harris Chi Ho C. | Director of Data Engineering, Internet, Mid-Market (51-1000 emp.) **Reviewed Date:** April 15, 2015 **What do you like best about Rocket Vertica?** The columnar storage enables to calculate metrics pretty quickly even in billions of rows. **What do you dislike about Rocket Vertica?** The query optimizer is not as great as postgresql and other traditional RDBMS. It would require external in memory help for speedy data report for external consumers. **Recommendations to others considering Rocket Vertica:** Consider to have more testing when release a major version. the experience was pleasant when we switch from 6.3 to 7 **What problems is Rocket Vertica solving and how is that benefiting you?** Internal and external reporting for ad tech company. The benefit is it abstracts the sharding needs when using relation dbms such as mysql/postgres ### 15. HP Vertica - Columnar Database **Rating:** 5.0/5.0 stars **Reviewed by:** Rajasekhar Y. | Director of Data Architecture, Internet, Mid-Market (51-1000 emp.) **Reviewed Date:** April 06, 2015 **What do you like best about Rocket Vertica?** - Columnar Architecticted Database - Works with Regular Infrastructure **What do you dislike about Rocket Vertica?** - Lack of inbuilt tools for Data LifeCycle Management **Recommendations to others considering Rocket Vertica:** Understand Vertica. Understand your business Problem. If your problem fits Vertica, Go for it. It is a great product at the time within the columnar databases as such, which aptly fits the needs of Datawarehousing/ Analytic Team needs. **What problems is Rocket Vertica solving and how is that benefiting you?** Managing big data with speed it calls for is realized with Vertica. And its a great software for analytic team needs as well. ### 16. Great for big data **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Capital Markets | Mid-Market (51-1000 emp.) **Reviewed Date:** October 03, 2012 **What do you like best about Rocket Vertica?** Handles a TON of data and is super fast and cheap for the amount of data it can hold. Querying a 500+ million row table is no problem. It's great for archival data. **What do you dislike about Rocket Vertica?** Joins are a little clunky and slow. Performance may vary overall based on how well the system is fine-tuned to your needs. Fine-tuning requires some skill. **Recommendations to others considering Rocket Vertica:** If you have a lot of data and need to be able to access it quickly, then Vertica may work for you. If not, you'll probably be better off going with a more common/easier to set-up database system. ## Rocket Vertica Discussions - [What offerings are there to run it in AWS cloud?](https://www.g2.com/discussions/what-offerings-are-there-to-run-it-in-aws-cloud) - 1 comment, 1 upvote - [need to check](https://www.g2.com/discussions/36279-need-to-check) - 1 comment, 1 upvote - [More and more technical documentation should be available for](https://www.g2.com/discussions/34471-more-and-more-technical-documentation-should-be-available-for) - 1 comment, 1 upvote - [How do I learn advanced methods and tuning of queries for free by vertica official](https://www.g2.com/discussions/34344-how-do-i-learn-advanced-methods-and-tuning-of-queries-for-free-by-vertica-official) - 1 comment, 1 upvote - [Is it hard to learn to be a Vertica user? Admin?](https://www.g2.com/discussions/user-friendly) - 2 comments, 1 upvote - [View Rocket Vertica pricing details and edition comparison](https://www.g2.com/products/rocket-vertica/reviews?page=5§ion=pricing&secure%5Bexpires_at%5D=2026-08-07+11%3A00%3A34+-0500&secure%5Bsession_id%5D=21862211-910f-4412-95e2-9d79cfb3ef71&secure%5Btoken%5D=e7129555f1e2c8661e401cca6f21bce477ccf1f07bfe576158ded6728d100ddd&format=llm_user) ## Rocket Vertica Features **Data Management** - Data Integration - Data Compression - Data Quality - Built-In Data Analytics - In-Database Machine Learning - Data Lake Analytics **Storage** - Data Model - Data Types **Database** - Real-Time Data Collection - Data Distribution - Data Lake **Integration** - AI/ ML Integration - BI Tool Integration - Data lake Integration **Availability** - Auto Sharding - Auto Recovery - Data Replication **Integrations** - Hadoop Integration - Spark Integration **Deployment** - On-Premise - Cloud **Performance** - Integrated Cache **Platform** - Machine Scaling - Data Preparation - Spark Integration **Performance ** - Scalability **Security** - Role-Based Authorization - Authentication - Audit Logs - Encryption **Processing** - Cloud Processing - Workload Processing **Security** - Data Governance - Data Security **Support** - Multi-Model - Operating Systems **Generative AI** - AI Text Generation - AI Text Summarization - Generative AI **Additional Functionality** - Parallel Processing - Ad hoc Analysis - Multiple Data Sources - API - In-Database Processing - Monitoring - Real-Time Reporting - Data Synchronization - Real-Time Monitoring - Data Connectors - Performance Metrics - Ad hoc Reporting - Alerts/Notifications - Access Controls/Permissions - Drag & Drop - Data Visualization - Data Import/Export - Match & Merge - Data Transformation - Secure Data Storage - Data Extraction - AI Copilot - Customizable Reports - Activity Dashboard - Data Migration - In-Memory Processing - Data Mapping **Building Reports** - Data Transformation - Data Modeling - WYSIWYG Report Design - Integration APIs - Real-Time Data - Real-Time Data - Third-Party Integrations **Platform** - Mobile User Support - Customization - User, Role, and Access Management - Internationalization - Sandbox / Test Environments - Performance and Reliability - Breadth of Partner Applications - Mobile Access - Metadata Management ## Top Rocket Vertica Alternatives - [Google Cloud BigQuery](https://www.g2.com/products/google-cloud-bigquery/reviews) - 4.5/5.0 (1,144 reviews) - [Snowflake](https://www.g2.com/products/snowflake/reviews) - 4.5/5.0 (713 reviews) - [Amazon Redshift](https://www.g2.com/products/amazon-redshift/reviews) - 4.3/5.0 (371 reviews)