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Neo4j Graph Database vs OpenText Analytics Database (Vertica) comparison

 

Comparison Buyer's Guide

Executive Summary

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

Neo4j Graph Database
Average Rating
8.6
Reviews Sentiment
7.7
Number of Reviews
6
Ranking in other categories
NoSQL Databases (10th)
OpenText Analytics Database...
Average Rating
8.2
Reviews Sentiment
6.9
Number of Reviews
90
Ranking in other categories
Data Warehouse (5th), Cloud Data Warehouse (11th)
 

Featured Reviews

RT
VP odfTechnology at Enterpi Software Solutions Private Limited
Delivers superior search and data aggregation capabilities
Neo4j helps with advanced search needs, providing good search results and aggregates compared to MongoDB. Aggregating with MongoDB can be difficult; however, with Neo4j, it's easier. Aggregating data, backing up, and creating new clusters are user-friendly from the back end. In DevOps web deployment, we noticed no database issues. We created Docker instances and set them up efficiently, managing databases up to 50 gigabytes.
JN
consultant at tcs
Data warehousing has transformed reporting performance and now delivers near real-time insights
OpenText Analytics Database (Vertica) is a very powerful analytic database, but like any platform, there are areas where it can improve to make daily work even smoother. Better cloud-native experience is one area for improvement. OpenText Analytics Database (Vertica) was originally designed as an on-premises analytic database and later moved to cloud. Improvement opportunities include more seamless cloud-native features such as auto-scaling, serverless options, and easier cluster management. Competitors such as Snowflake and BigQuery provide more fully managed experiences. Easier UI is another area for improvement. Most administration is currently done by SQL and command line tools. An improvement opportunity would be a more modern web UI for monitoring, workload management, and troubleshooting. Faster ecosystem and community growth is needed. In short, OpenText Analytics Database (Vertica) could improve in areas such as cloud-native capability, modern UI for administration, stronger real-time streaming integration, and growing its ecosystem and community. These enhancements would make it easier to manage and adopt compared to newer cloud-first analytic platforms. From a day-to-day operational perspective, there are a few areas where OpenText Analytics Database (Vertica) could improve to make our work smoother. Smarter automatic projection management is needed with more intelligence, auto projection creation, automatic optimization, and reduced manual testing with better workload management. Right now, monitoring queries often requires system tables and manual analysis. Troubleshooting slow queries takes time. A modern real-time dashboard showing query bottlenecks and resource users would enable quick detection. The impact could be faster issue resolution and less time spent debugging performance. Storage native interaction with modern data tools is also important. In short, from a day-to-day perspective, improvements in automatic projection optimization, better workload monitoring dashboard, easier schema evolution, and stronger modern tool integration would significantly reduce manual tuning effort and improve developer productivity. While OpenText Analytics Database (Vertica) is very powerful, these enhancements would make it more efficient for the analytics team.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"Creates the ability to visualize outputs."
"Neo4j helps with advanced search needs, providing good search results and aggregates compared to MongoDB."
"The solution's best feature is how it differs from traditional SQL databases. It's hard to map people and find those near me in SQL, which requires long, complex queries. Neo4j Graph Database makes this easier with simpler queries. It also supports more data types, like JSON, which SQL doesn't."
"Enables people to understand what the business problem is and how the technology helps."
"The graph modeling paradigm suits our data set well, where there may be orders of magnitude more connections between data points than data points themselves."
"As a graph database, I am surprised at their performance and response time."
"It enables circumstances which would have been a complex problem to be simplified."
"For now, the tool doesn't break down or stop, so it is quite stable."
"The fast columnar store database structure allows our query times to be at least 10x faster than on any other database."
"Vertica is easy to use and provides really high performance, stability, and scalability."
"For me, It's performance, scalability, low cost, and it's integrated into enterprise and big data environments."
"We use Vertica as our primary data warehouse."
"The most valuable feature of Vertica is the unmatchable database performance at a fraction of cost compared to other similar databases."
"Vertica is very robust and recovers predictably from unexpected infrastructure failures."
"The feature I like best is performance. We use Red Tool and Red Job for the data warehouse and reporting. It's perfect. Performance is good, and it can return ad hoc queries very quickly. Of course, it's a cluster, so it's easy to scale."
"OpenText Analytics Database (Vertica) has impacted my organization a lot in terms of driving the key results and giving the key insights to the leadership, and through those data points, a good amount of decisions have been made which was really helpful and impactful at an organizational level."
 

Cons

"The only problem is that the community is quite small."
"The tool could improve by having more resources, especially for Golang, which we use. It lacks good basic libraries and doesn't have an ORM (Object-Relational Mapping) tool, which many NoSQL databases have. We thought about building an ORM for the Neo4j Graph Database but are too busy."
"There are concerns about performance and whether the tool can necessarily scale to provide the solution."
"So far, we have not had any issues and are happy with the product in general."
"There are things I found unintuitive or difficult to understand, however I can't say this is a deficiency in the product and likely more a function of my relatively low experience."
"For me, when the tool was deployed on an on-premises model, it was a little bit difficult the first time."
"When it is about to reach the maximum storage capacity, it becomes slow."
"Node recovery is very inconsistent and impacts performance."
"Machine learning implementations."
"OpenText Analytics Database (Vertica) does not support hard delete, and they perform soft delete, which is the case with all columnar databases."
"Fact-to-fact joins on multi-billion record tables perform poorly."
"Their support is really bad. Maybe Micro Focus has changed but they were not good before."
"We had confronted couple of issues during Vertica upgrades for which we do align with your support group."
"vbr.py needs to be improve to support diff no of nodes source to target."
 

Pricing and Cost Advice

"The solution is open source so that you can use it for free. They also offer an enterprise version with its billing. If your company is earning well, I suggest using the enterprise version. Otherwise, you can deploy it on your own cloud and pay based on usage."
"The tool is not expensive."
"The first TB is free and you can use all the Vertica features. After 1TB you have to pay for licensing. The product is worth it, but be aware of this condition, and plan. The compression ratio is explained in the documentation."
"The price is reasonable. We use a pay per license model. Firstly, you need to buy a license. After that, you mainly pay the annual support fee of around 20% or 25%. I think their prices are quite reasonable."
"The pricing and licensing depend on the size of your environment and the zone where you want to implement."
"I am aware that we have licensed it, but I have no knowledge of its cost."
"From a cost perspective, the software is less than most of its competitors."
"Work with a vendor, if possible, and take advantage of more aggressive discounts at mid-fiscal year (April) and fiscal year-end (October).​"
"Vertica is an expensive tool."
"It's difficult today to compete with open-source solutions. In these areas, there is a lot of competition and the price of this solution is a bit pricy."
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Top Industries

By visitors reading reviews
Financial Services Firm
14%
Construction Company
10%
University
7%
Computer Software Company
7%
Financial Services Firm
16%
Outsourcing Company
9%
Computer Software Company
8%
Manufacturing Company
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business29
Midsize Enterprise23
Large Enterprise43
 

Questions from the Community

What is your experience regarding pricing and costs for Neo4j?
The solution is open source so that you can use it for free. They also offer an enterprise version with its billing. If your company is earning well, I suggest using the enterprise version. Otherwi...
What needs improvement with Neo4j Graph Database?
The only problem is that the community is quite small.
What is your primary use case for Neo4j Graph Database?
We have used Neo4j in microservices. In one of the microservices, we used Neo4j since we have some requirements similar to MongoDB plus Elasticsearch. It performs both functions. Instead of doing t...
What is your experience regarding pricing and costs for Vertica?
My experience with pricing, setup cost, and licensing is limited because the organization handled the licensing and pricing as well as the cost setup.
What needs improvement with Vertica?
OpenText Analytics Database (Vertica) is already doing great. There could be a community which could have been much more advanced and more people can be engaged so that any kind of questions, queri...
What is your primary use case for Vertica?
The main use case for OpenText Analytics Database (Vertica) is that we have the Hive and a Hadoop layer for data availability, and Vertica serves as a big data solution. Within a Hive table, OpenTe...
 

Also Known As

No data available
Micro Focus Vertica, HPE Vertica, HPE Vertica on Demand
 

Overview

 

Sample Customers

Walmart, Telenor, Wazoku, Adidas, Cerved, GameSys, eBay, Schleich, ICIJ, die Bayerisch, Megree, InfoJobs, LinkedIn
Cerner, Game Show Network Game, Guess by Marciano, Supercell, Etsy, Nascar, Empirix, adMarketplace, and Cardlytics.
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