OpenText Analytics Database (Vertica) and Microsoft Azure Synapse Analytics are both prominent in the data analytics and management sector. While Vertica demonstrates strong capabilities in handling Very Large Databases with cost-efficient storage, Azure Synapse offers superior integration with Microsoft services and user-friendliness.
Features: Vertica is praised for its fast data loading capabilities, cost-efficient storage, and impressive clustering and compression. It handles concurrent queries efficiently and offers SQL compatibility with sophisticated analytics features. Microsoft Azure Synapse is recognized for its seamless integration within Azure services, comprehensive analytics, and scalability. It also integrates well with Power BI and offers a flexible cloud-based infrastructure.
Room for Improvement: Vertica users seek better transaction handling, workload management, and database size configuration options. There is a need for better documentation and developer tools. Microsoft Azure Synapse users desire improved data governance and security, more advanced analytical features, and enhanced integration with non-Microsoft systems, as well as better cost control measures.
Ease of Deployment and Customer Service: Vertica offers versatile deployment options on-premises and on hybrid and public clouds. Customer service is strong, though there are varied reports on technical support quality. Microsoft Azure Synapse is widely used in public and hybrid clouds, benefiting from strong Microsoft integration with reliable customer service, though some challenges exist in technical expertise and resolution times.
Pricing and ROI: Vertica provides a transparent licensing model based on storage size, known for cost-effectiveness and high ROI despite being seen as expensive. It is valued for enhanced analytics and user satisfaction. Microsoft Azure Synapse employs a pay-as-you-go model with flexible but potentially unpredictable billing, and while some users find costs high, the product is acknowledged for its robust performance and potential for substantial returns.
Not monitoring data results often in a big impact on customer services and customer perception.
They are slow to respond and not very knowledgeable.
For the scalability of Microsoft Azure Synapse Analytics, I would rate it a 10 until you remain in the Azure Cloud scalability framework.
Microsoft Azure Synapse Analytics is scalable, offering numerous opportunities for scalability.
I find the service stable as I have not encountered many issues.
Databricks is a very rich solution, with numerous open sources and capabilities in terms of extract, transform, load, database query, and so forth.
There is a need for better documentation, particularly for customized tasks with Microsoft Azure Synapse Analytics.
When you scale the solution, the cloud doesn't work anymore in terms of cost.
For Microsoft Azure Synapse Analytics, the integration is the most valuable feature, meaning that whatever you need is fast and easy to use.
Microsoft Azure Synapse Analytics offers significant visibility, which helps us understand our usage more clearly.
Microsoft Azure Synapse Analytics is an end-to-end analytics solution that successfully combines analytical services to merge big data analytics and enterprise data warehouses into a single unified platform. The solution can run intelligent distributed queries among nodes, and provides the ability to query both relational and non-relational data.
Microsoft Azure Synapse Analytics is built with these 4 components:
Microsoft Azure Synapse Analytics Features
Microsoft Azure Synapse Analytics has many valuable key features, including:
Microsoft Azure Synapse Analytics Benefits
Some of the benefits of using Microsoft Azure Synapse Analytics include:
Reviews from Real Users
Below are some reviews and helpful feedback written by Microsoft Azure Synapse Analytics users who are currently using the solution.
PeerSpot user Jael S., who is an Information Architect at Systems Analysis & Design Engineering, comments on her experience using the product, saying that it is “Scalable, intuitive, facilitates compliance and keeps your data secure”. She also says "We also like governance. It looks at what the requirements are for the company to identify the best way to ensure compliance is met when you move to the cloud."
Michel T., CHTO at Timp-iT, mentions that "the features most valuable are the simplicity, how easy it is to create a dashboard from different information systems."
A Senior Teradata Consultant at a tech services company says, "Microsoft provides both the platform and the data center, so you don't have to look for a cloud vendor. It saves you from having to deal with two vendors for the same task."
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.
We monitor all Cloud Data Warehouse reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
