OpenText Analytics Database (Vertica) and Azure Synapse Analytics compete in the analytics database category. Based on feature-rich integration and user-friendly environment, Azure Synapse Analytics seems to have the upper hand.
Features: OpenText Analytics Database (Vertica) is known for its speed and performance, managing vast data efficiently with support for SQL queries and OLAP operations. It utilizes columnar storage and projection features ideal for complex analytics on large datasets. Additionally, it offers clustering support. Azure Synapse Analytics integrates seamlessly with Azure services, provides robust scalability, various integration options, and a user-friendly platform.
Room for Improvement: Vertica could enhance workload management, improve documentation, and offer better support for complex query optimization. There is also a need for improved integration with other systems and advancements in machine learning capabilities. Azure Synapse Analytics could benefit from better query caching, enhanced ease of use, and improved integration with non-Microsoft products. Users seek better governance features and easier migration and configuration.
Ease of Deployment and Customer Service: Vertica allows deployment across private, public, and hybrid clouds with generally satisfactory user feedback, although support quality can vary. Azure Synapse Analytics offers seamless public cloud deployment with strong integration into Microsoft's ecosystem. While its customer service is considered adequate, enhancement in global support reach and engagement is desired.
Pricing and ROI: Vertica has a transparent pricing model based on data size, appreciated for cost-effectiveness despite being somewhat expensive. The performance benefits and perpetual license model are favored. Azure Synapse Analytics uses a pay-as-you-go model, potentially leading to cost unpredictability but offers value through integration with Microsoft tools. Both solutions provide potential ROI improvements over traditional systems.
Some of my customers have indeed seen a return on investment with Microsoft Azure Synapse Analytics as they used it for analytics to drive decision-making, improving their processes or increasing revenue.
This is an underestimation of the real impact because we use big data also to monitor the network and the customer.
They are slow to respond and not very knowledgeable.
I would rate the support for Microsoft Azure Synapse Analytics as an eight out of ten.
There was no way to scale concurrent querying in too much detail, as all jobs get submitted to Microsoft Azure Synapse Analytics in sequence.
Microsoft Azure Synapse Analytics is scalable, offering numerous opportunities for scalability.
Recovering from such scenarios becomes a bit problematic or time-consuming.
I find the service stable as I have not encountered many issues.
We have never integrated Microsoft Azure Synapse Analytics with Databricks, but we have mostly pulled data from on-premises systems into Azure Databricks.
There is a need for more expertise among the support team to guide us effectively.
Sometimes, when jobs are running in production, it might show some faults, and recovering from such scenarios becomes a bit problematic or time-consuming.
The scalability of Microsoft Azure Synapse Analytics is a concern, depending on the size of the data warehouse to be built.
The cheapest tier costs about $4,000 to $4,700 a year, while the most expensive tier can reach up to $300,000 a year.
I think the price of Microsoft Azure Synapse Analytics is very expensive, but that's not only for Microsoft Azure Synapse Analytics—it's for the cloud in general.
I find the pricing of Microsoft Azure Synapse Analytics reasonable.
One of the most valuable features in Microsoft Azure Synapse Analytics is the ability to write your own ETL code using Azure Data Factory, which is a component within Synapse.
Fabric is much better compared to Microsoft Azure Synapse Analytics because you can properly separate out data and compute.
The best feature of Microsoft Azure Synapse Analytics is the notebook functionality; it provides a very good interface, and we can easily do our experiments, POCs, and check things before migration or deployment to higher environments such as from development to SIT and then production.
Product | Market Share (%) |
---|---|
Microsoft Azure Synapse Analytics | 6.3% |
OpenText Analytics Database (Vertica) | 6.1% |
Other | 87.6% |
Company Size | Count |
---|---|
Small Business | 29 |
Midsize Enterprise | 18 |
Large Enterprise | 55 |
Company Size | Count |
---|---|
Small Business | 29 |
Midsize Enterprise | 23 |
Large Enterprise | 38 |
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.
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