OpenText Analytics Database (Vertica) and Amazon Redshift compete in the cloud analytics and data warehousing category. Vertica seems to have the upper hand in feature robustness and handling massive data scales, while Redshift excels in integration within the AWS ecosystem and ease of setup.
Features: Vertica is noted for its advanced analytics capabilities, strong scalability, and efficient concurrent query handling. It provides robust clustering and compression features. Amazon Redshift offers quick scalability, multi-formatted data accessibility, and strong cloud integration, which are significant for seamless data warehouse operations.
Room for Improvement: Vertica could benefit from enhanced workload management and better documentation. There's a need for improved transaction handling and automation of administrative tasks. Redshift faces cost challenges in large-scale operations and requires improvements in security integration and regional availability for snapshots. Simplifying its ETL process could also enhance efficiency.
Ease of Deployment and Customer Service: Vertica offers versatile deployment options, including on-premises and hybrid clouds, although it needs better deployment documentation. Its customer service has mixed reviews, particularly since its acquisition. Amazon Redshift operates smoothly within the public cloud, benefiting from AWS integrations and community support, despite slow response times and costly higher-tier support.
Pricing and ROI: Vertica has a flexible licensing model based on data size, appealing for long-term use. Its efficiency and performance deliver significant ROI for larger operations. Redshift offers a pay-as-you-go model, providing financial flexibility and competitive costs for large-scale cloud operations.
Whenever we need support, if there is an issue accessing stored data due to regional data center problems, the Amazon team is very helpful and provides optimal solutions quickly.
It's costly when you enable support.
The scalability part needs improvement as the sizing requires trial and error.
Amazon Redshift is a stable product, and I would rate it nine or ten out of ten for stability.
They should bring the entire ETL data management process into Amazon Redshift.
Integration with AI could be a good improvement.
The cost of technical support is high.
It's a pretty good price and reasonable for the product quality.
The pricing of Amazon Redshift is expensive.
Amazon Redshift's performance optimization and scalability are quite helpful, providing functionalities such as scaling up and down.
Scalability is the best feature of Amazon Redshift. Amazon Redshift handles scalability automatically, so we do not need to scale up or down; it is all managed by Redshift.
Scalability is also a strong point; I can scale it however I want without any limitations.
Amazon Redshift is a fully administered, petabyte-scale cloud-based data warehouse service. Users are able to begin with a minimal amount of gigabytes of data and can easily scale up to a petabyte or more as needed. This will enable them to utilize their own data to develop new intuitions on how to improve business processes and client relations.
Initially, users start to develop a data warehouse by initiating what is called an Amazon Redshift cluster or a set of nodes. Once the cluster has been provisioned, users can seamlessly upload data sets, and then begin to perform data analysis queries. Amazon Redshift delivers super-fast query performance, regardless of size, utilizing the exact SQL-based tools and BI applications that most users are already working with today.
The Amazon Redshift service performs all of the work of setting up, operating, and scaling a data warehouse. These tasks include provisioning capacity, monitoring and backing up the cluster, and applying patches and upgrades to the Amazon Redshift engine.
Amazon Redshift Functionalities
Amazon Redshift has many valuable key functionalities. Some of its most useful functionalities include:
Reviews from Real Users
“Redshift's versioning and data security are the two most critical features. When migrating into the cloud, it's vital to secure the data. The encryption and security are there.” - Kundan A., Senior Consultant at Dynamic Elements AS
“With the cloud version whenever you want to deploy, you can scale up, and down, and it has a data warehousing capability. Redshift has many features. They have enriched and elaborate documentation that is helpful.”- Aishwarya K., Solution Architect at Capgemini
OpenText Analytics Database Vertica is known for its fast data loading and efficient query processing, providing scalability and user-friendliness with a low cost per TB. It supports large data volumes with OLAP, clustering, and parallel ingestion capabilities.
OpenText Analytics Database Vertica is designed to handle substantial data volumes with a focus on speed and efficient storage through its columnar architecture. It offers advanced performance features like workload isolation and compression, ensuring flexibility and high availability. The database is optimized for scalable data management, supporting data scientists and analysts with real-time reporting and analytics. Its architecture is built to facilitate hybrid deployments on-premises or within cloud environments, integrating seamlessly with business intelligence tools like Tableau. However, challenges such as improved transactional capabilities, optimized delete processes, and better real-time loading need addressing.
What features define OpenText Analytics Database Vertica?OpenText Analytics Database Vertica's implementation spans industries such as finance, healthcare, and telecommunications. It serves as a central data warehouse offering scalable management, high-speed processing, and geospatial functions. Companies benefit from its capacity to integrate machine learning and operational reporting, enhancing analytical capabilities.
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