Find out what your peers are saying about Snowflake Computing, Microsoft, Google and others in Cloud Data Warehouse.
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.
We have realized a return on investment, with a reduction of staff from 27 to eight, and our current return on investment is approximately 14%.
They are slow to respond and not very knowledgeable.
This is an underestimation of the real impact because we use big data also to monitor the network and the customer.
I would rate the support for Microsoft Azure Synapse Analytics as an eight out of ten.
I received great support in migrating data to Snowflake, with quick responses and innovative solutions.
The technical support from Snowflake is very good, nice, and efficient.
The customer support for Teradata has been great.
Customer support is very good, rated eight out of ten under our essential agreement.
The technical support from Teradata is quite advanced.
Microsoft Azure Synapse Analytics is scalable, offering numerous opportunities for scalability.
For the scalability of Microsoft Azure Synapse Analytics, I would rate it a 10 until you remain in the Azure Cloud scalability framework.
Recovering from such scenarios becomes a bit problematic or time-consuming.
Snowflake is very scalable and has a dedicated team constantly improving the product.
The billing doubles with size increase, but processing does not necessarily speed up accordingly.
This expansion can occur without incurring downtime or taking systems offline.
Scalability is complex as you need to purchase a license and coordinate with Teradata for additional disk space and CPU.
Teradata's scalability is great; it's been awesome.
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.
Snowflake is very stable, especially when used with AWS.
Snowflake as a SaaS offering means that maintenance isn't an issue for me.
I find the stability to be almost a ten out of ten.
The workload management and software maturity provide a reliable system.
There is a need for better documentation, particularly for customized tasks with Microsoft Azure Synapse Analytics.
Databricks is a very rich solution, with numerous open sources and capabilities in terms of extract, transform, load, database query, and so forth.
The reasons I don't rate Microsoft Azure Synapse Analytics higher include data integration and tech support being two main issues.
Enhancements in user experience for data observability and quality checks would be beneficial, as these tasks currently require SQL coding, which might be challenging for some users.
Cost reduction is one area I would like Snowflake to improve.
Unlike SQL and Oracle, which have in-built replication capabilities, we don't have similar functionality with Teradata.
The most challenging aspect is finding Teradata resources, so we are focusing on internal training and looking for more Teradata experts.
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.
Snowflake's pricing is on the higher side.
Snowflake lacks transparency in estimating resource usage.
Teradata is much more expensive than SQL, which is well-performed and cheaper.
Initially, it may seem expensive compared to similar cloud databases, however, it offers significant value in performance, stability, and overall output once in use.
We spent roughly $295,000 on setup costs.
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.
Microsoft Azure Synapse Analytics offers significant visibility, which helps us understand our usage more clearly.
For Microsoft Azure Synapse Analytics, the integration is the most valuable feature, meaning that whatever you need is fast and easy to use.
Snowflake is a data lake on the cloud where all processing happens in memory, resulting in very fast query responses.
The independence of the compute and storage within Snowflake is key.
Teradata's security helps our organization meet compliance requirements such as GDPR and IFRS, and it is particularly essential for revenue contracting or revenue recognition.
The data mover is valuable over the last two years as it allows us to achieve data replication to our disaster recovery systems.
Product | Market Share (%) |
---|---|
Snowflake | 17.7% |
Teradata | 8.5% |
Microsoft Azure Synapse Analytics | 6.3% |
Other | 67.5% |
Company Size | Count |
---|---|
Small Business | 29 |
Midsize Enterprise | 18 |
Large Enterprise | 55 |
Company Size | Count |
---|---|
Small Business | 28 |
Midsize Enterprise | 20 |
Large Enterprise | 56 |
Company Size | Count |
---|---|
Small Business | 26 |
Midsize Enterprise | 12 |
Large Enterprise | 49 |
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."
Snowflake provides a modern data warehousing solution with features designed for seamless integration, scalability, and consumption-based pricing. It handles large datasets efficiently, making it a market leader for businesses migrating to the cloud.
Snowflake offers a flexible architecture that separates storage and compute resources, supporting efficient ETL jobs. Known for scalability and ease of use, it features built-in time zone conversion and robust data sharing capabilities. Its enhanced security, performance, and ability to handle semi-structured data are notable. Users suggest improvements in UI, pricing, on-premises integration, and data science functions, while calling for better transaction performance and machine learning capabilities. Users benefit from effective SQL querying, real-time analytics, and sharing options, supporting comprehensive data analysis with tools like Tableau and Power BI.
What are Snowflake's Key Features?In industries like finance, healthcare, and retail, Snowflake's flexible data warehousing and analytics capabilities facilitate cloud migration, streamline data storage, and allow organizations to consolidate data from multiple sources for advanced insights and AI-driven strategies. Its integration with analytics tools supports comprehensive data analysis and reporting tasks.
Teradata is a powerful tool for handling substantial data volumes with its parallel processing architecture, supporting both cloud and on-premise environments efficiently. It offers impressive capabilities for fast query processing, data integration, and real-time reporting, making it suitable for diverse industrial applications.
Known for its robust parallel processing capabilities, Teradata effectively manages large datasets and provides adaptable deployment across cloud and on-premise setups. It enhances performance and scalability with features like advanced query tuning, workload management, and strong security. Users appreciate its ease of use and automation features which support real-time data reporting. The optimizer and intelligent partitioning help improve query speed and efficiency, while multi-temperature data management optimizes data handling.
What are the key features of Teradata?In the finance, retail, and government sectors, Teradata is employed for data warehousing, business intelligence, and analytical processing. It handles vast datasets for activities like customer behavior modeling and enterprise data integration. Supporting efficient reporting and analytics, Teradata enhances data storage and processing, whether deployed on-premise or on cloud platforms.