OpenText Analytics Database Vertica and Snowflake Analytics are strong contenders in the data analytics domain. Vertica seems to have an advantage in pricing and efficiency, while Snowflake is recognized for its robust features and ease of data sharing.
Features: Vertica is noted for its fast data handling capabilities, clustering for commodity hardware, and low storage costs which are ideal for managing large data volumes. Snowflake excels with cloud-native scalability, a user-friendly interface, and features like time travel that enhance data manipulation flexibility.
Room for Improvement: Vertica could enhance its transactional handling, simplify management for new users during peak loads, and improve machine learning support. Snowflake might improve machine learning integration, offer better large dataset handling, and ensure more transparent pricing models.
Ease of Deployment and Customer Service: Vertica offers flexible deployment across on-premises and hybrid environments but might be complex for beginners. Snowflake’s cloud-based deployment is praised for ease and simple scaling. Vertica's customer service shows mixed reviews, whereas Snowflake is often rated well for proactive support.
Pricing and ROI: Vertica provides competitive pricing that is particularly advantageous for long-term storage, focusing on data size, which users find cost-effective. Snowflake’s flexible pricing, based on storage and compute usage, can result in high costs if not optimized. However, both solutions are seen as providing good ROI, with Vertica delivering performance benefits and Snowflake offering extensive scalability.
The technical support for Snowflake Analytics is excellent based on what I have heard from others.
It supports both horizontal and vertical scaling effectively.
Storage is unlimited because they use S3 if it is AWS, so storage has no limit.
Snowflake Analytics is stable, scoring around eight point five to nine out of ten.
If it offered flexibility similar to Oracle and supported more heterogeneous data sources and database connectivity, it would be even better.
AIML-based SQL prompt and query generation could be an area for enhancement.
Navigating the user console can be challenging, particularly when looking for details like the account ID.
Snowflake charges per query, which amounts to a very minor cost, such as $0.015 per query.
Snowflake is better and cheaper than Redshift and other cloud warehousing systems.
Snowflake Analytics is quite economical.
Running a considerable query on Microsoft SQL Server may take up to thirty minutes or an hour, while Snowflake executes the same query in less than three minutes.
Snowflake Analytics supports data security with a single sign-on feature and complies with framework regulations, which is highly beneficial.
It is a data offering where I can see data lineage, data governance, and data security.
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.
Conventional data platforms and big data solutions struggle to deliver on their fundamental purpose: to enable any user to work with any data, without limits on scale, performance or flexibility. Whether you’re a data analyst, data scientist, data engineer, or any other business or technology professional, you’ll get more from your data with Snowflake.
To achieve this, we built a new data platform from the ground up for the cloud. It’s designed with a patented new architecture to be the centerpiece for data pipelines, data warehousing, data lakes, data application development, and for building data exchanges to easily and securely share governed data. The result, A platform delivered as a service that’s powerful but simple to use.
Snowflake’s cloud data platform supports a multi-cloud strategy, including a cross-cloud approach to mix and match clouds as you see fit. Snowflake delivers advantages such as global data replication, which means you can move your data to any cloud in any region, without having to re-code your applications or learn new skills.
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