Data sharing is a good feature. It is a majorly used feature. The elastic compute is another big feature. Separating compute and storage gives you flexibility. 

It doesn't require much DBA involvement because it doesn't need any performance tuning. We are not really doing any performance tuning, and the entire burden of performance tuning and SQL tuning is on Snowflake.

Its usability is very good. I don't need to ramp up any user, and its onboarding is easier. You just onboard the user, and you are done with it. There are simple SQL and UI, and people are able to use this solution easily. Ease of use is a big thing in Snowflake.

Time travel is one feature that really helps us out. If there is some data discrepancy or something wrong that happens with the table, at any point, we can get that data back and time travel via fail-safe features. They're really good. 

The feasibility to increase horizontal or vertical scaling is great. It really helps a developer at an enterprise level. If you're considering scaling, it won't take much time. 

We can create cloning via Snowflake. There's a lot of time savings.

The initial setup is simple. 

I found Snowflake's performance to be its most valuable feature. The product is an incredibly fast and performant data warehouse. We handle a lot of semi-structured data natively with it, which is nice. 

I also appreciate Snowflake's scalability. As the company has grown, as the number of Snowflake users have grown, I have not had any issue scaling.

One of Snowflake’s most valuable features is that you don't need to worry about computing. You don't need to scale up the compute size. When you are using a compute pay-per-use model and the storage is cheap, the data can go from terabytes to petabytes. In this case, you don't need to procure any new hardware or software, it automatically scales up.

Snowflake is user-friendly and reliable in creating the data warehouse and carrying out data modeling. 

The query speed, and the way that it actually executes its queries is the most valuable aspect of the solution. We had some queries that would take hours upon hours to run, and the Snowflake returns the results in about 15 minutes.

It requires no maintenance on our part. They handle all that. The speed is phenomenal. The pricing isn't really anything more than what you would be paying for a SQL server license or another tool to execute the same thing. We have zero maintenance on our side to do anything and the speed at which it performs queries and loads the data is amazing. It handles unstructured data extremely well, too. So, if the data is in a JSON array or an XML, it handles that super well.

It's a good tool. It is quite easy to manage. 

There are a lot of features. 

If you accidentally delete something, you can time travel and retrieve it. 

Within half an hour or even 15 minutes, you can set up a new data warehouse, and you can clone a table or whatever you like. 

It's easy to provide access to clients if they need to.

The solution is stable. 

It can scale well.

There is good online documentation via the community, and you can learn the solution on your own. 

The product is quite fast. There are several connectors in Snowflake that we could leverage for ingesting data. The data could be in zettabytes or petabytes. It is easily manageable.

The features I have found most valuable are the options to connect with extendable sources in three buckets in which we can also create stages.

Everything is automatic, and I don't have to do any maintenance.

All the features of the product that are needed for the data warehouse are good. The solution enables the ingestion of data and the usability of preferred languages while creating the data. The performance of the engine is good. The solution speeds up the process of onboarding. We can connect to different sources and get the data very fast. 

The tool does a very good job in reporting and data transformation. We can adapt it well to our needs. When we try to ingest data from many sources, it helps harmonize the data sources. It also helps with duplication and cleaning of the data. It is a pretty difficult and time-consuming task, and Snowflake helps us with it.

In my view, cost optimization for the computing power required by the ETL jobs, reports, and dashboards is the most valuable feature. Especially for startups, this helps us to keep cost spending within control without having to worry about manually shutting down the server when not used.  

As a Google partner, we like to leverage GCP (Google Cloud Platform). Snowflake supports GCP, AWS & Azure platforms. This works just fine for us. Encryption of data with multiple keys for both data in transit and data at rest gives us enough confidence to use snowflake for our customer 360 solutions.

I appreciate the Snowflake marketplace, where you can drop data and allow other people throughout the world to access it. You can go to the Snowflake marketplace and connect to some data. If somebody else publishes, for example, COVID-19 data or weather data, you can sign up for new data sets and bring them into your warehouse, which I found very interesting.

You can connect to different cloud sources, including Azure and AWS. 

You can report out, and all the cloud technologies have connected to Snowflake, allowing you to move the data or get the data into Snowflake. 

The initial setup was pretty simple. 

It scales really well. 

The solution is stable. 

The solution is reasonably priced. 

The most valuable feature has been the Snowflake data sharing and dynamic data masking.

The adaptation to development languages is most valuable. Our developers can SQL code or something else. It has been convenient in that regard.

The most valuable feature of Snowflake is consumption-based costs, which means that you only pay for the storage and compute you use. There's a complete separation of storage and computing, so you don't need to add another server to increase storage or computing. From a costing perspective, it's well-positioned. 

Snowflake's time travel is also incredibly useful, and they have a function called "UNDROP," where you can undo a table drop. Data sharing and replication for Snowflake are strong, and they have a data marketplace with public and private data sets available for sharing. Companies can put their data on the marketplace, and anyone can use it by starting the payment model. The data is provided live straight to you, and it appears as if it were just another database in your own environment.

The features I found most valuable with this solution are sharing options and built-in time zone conversion.

It's user-friendly. It's SQL-driven. The fact that business can also go to this application and query because they know SQL is the biggest factor. So, we can provide all the data, and the analysts, data scientists, and product strategists can go and analyze the data themselves.

It is a very good platform. It can handle structured and semi-structured data, and it can be used for your data warehouse or data lake. It can load and deal with any data that you have. It can extract data from an on-premises database or a website and make it available in the cloud.

It has very fast implementation and integration as compared to other solutions. There is no need for the DBA to manage or do the day-to-day DBA tasks, which is one of the greatest things about it.

Snowflake has three great features: Snowpiping is proving to be very valuable, Time Travel is excellent, and Snowpipes are another great functionality the solution has made available.

Snowflake's most valuable features are data enrichment and flattening.

• Computing unit is accessible via SQL: being able to turn them on or off as needed.
• Snowpipe (ingesting data)
• Looking back in time (being able to look at data in the past within a query)
• No data warehouse management
• Support for JSON.

The list is pretty long.

I like the ability to work with a managed service on the cloud and that is easy to start with.

The product's most important feature is unloading data to S3. It provides a single syntax query to analyze data directly from a database to an S3 bucket.

The solution's most valuable features are storage, run time, scalability, and minimum query time compared to other vendors.

The ability to share the data and the ability to scale up and down easily are the most valuable features. The concept of data sharing and data plumbing made it very easy to provide and share data. The ability to refresh your Dev or QA just by doing a clone is also valuable. It has the dynamic scale up and scale down feature. 

Development and deployment are much easier as compared to other platforms where you have to go through a lot of stuff. With a tool like DBT, you can do modeling and transformation within a single tool and deploy to Snowflake. It provides continuous deployment and continuous integration abilities.

There is a separation of storage and compute, so you only get charged for your usage. You only pay for what you use. When we share the data downstream with business partners, we can specifically create compute for them, and we can charge back the business.

It's ultra-fast at handling queries, which is what we find very convenient.

The pricing and licensing model is good.

The best thing about Snowflake is its flexibility in changing warehouse sizes or computational power. If I want to change the computation with other tools like Netezza, I would have to add a hard disk to it. With Snowflake, being on the AWS side, changing warehouses provides me with faster execution of my queries.

The vendor claims that the provision of warming sensors quickly enables warmth to compute nodes, which is their Unique Selling Point. From my experience, this has proven to be true.

The most valuable features of Snowflake are its performance and power.

I like the entire database. This is the advanced version of the cloud version, so it's really a flexible tool. If you have it implemented at home, you can access it from anywhere.

Snowflake has a variety of other ETL provisions that they provide. You can use your own ETL pipeline. Additionally, they provide adapters, and they are always evolving, it is a well-developed solution.

The way it is built and designed is valuable. The way the shared model is built and the way it exploits the power of the cloud is very good. Certain features related to administration and management, akin to Oracle Flashback and all that, are very important for modern-day administration and management.

It is also good in terms of managing and improving performance, indexing, and partitioning. It is sort of completely automated. Everything is essentially under the hood, and the engine takes care of it all. As a data warehouse on the cloud, Snowflake stands strong on its ground even though each of the cloud providers has its own data warehouse, such as Redshift for AWS or Synapse for Azure.

It is a very easy-to-use solution. It is user-friendly, and its setup time is very less.

The speed of data loading and being able to quickly create the environment are most valuable. 

For data, it provides built-in security and compliance with different standards, such as SOC 2, ISO, etc. So, we don't have to do a separate audit for compliance.

The most valuable feature is the clone copy.

I like Snowflake's data exchange capabilities. It can exchange data with downstream systems and other vendor partners as well.

Although I haven't used it much, it is very fast and the performance is great.

The tool is very easy to use. The solution’s desktop features are also very easy to use. Also, the product’s SQL-based connectivity is also good. It can connect with any tool.

It was relatively easy to use, and it was easy for people to convert to it. Moved 168 tables and appropriate indices to Snowflake with minimum modification to Current Oracle DDL. The largest degree of change was setting up the corresponding access Hierarchy to duplicate what was in Oracle ( customer had separate permission structures for application vs Admin/support vs direct reporting access to the data).

The most valuable feature of Snowflake is the query performance. Snowflake is the most efficient way for real-time dashboards or analytical business intelligence reports to be sent to the customer. There are a couple of areas where they have recently improved. One of the key features they introduced is an internal, table-based merch as well as storing of the unstructured data. You can now build a table out of unstructured data, metadata. This hasn't yet been officially announced.

In terms of features, we have not yet explored the product completely. So we are still in the proof of concept phase. As of now, the product meets our preliminary requirements. The snapshot feature is good and the rollback feature is good. That is why we have the product and these are the key things we need.

The most valuable feature of Snowflake is its performance. We can access the data quickly. Additionally, it handles structured and non-structured data.

Snowflake is an enormously useful platform. The Snowpipe feature is valuable because it allows us to load terabytes and petabytes of data into the data mart at a very low cost. Then we just share it out, and all the compute expenses are charged directly to our clients.

Snowflake has its own features in comparison to other similar solutions like Exadata. This gives it huge competitive power. It has a very good interface tool with its own benefits and features which are really useful for our needs from a computation and storage perspective. I think this solution provides the best potential of any data warehousing product where they choose to use Snowflake instead of Oracle or DBII. The product can be leveraged with respect to better performance, auto tuning, competition and performance. From an architectural perspective, the solution has all the ingredients it requires. 

The solution is easy to use. We have third-party integrations, which make it easy to migrate from our landing to our warehouse. Inside Snowflake, we can convert what we create, unlike other hyperscalers.

The feature that is really striking is the ability to translate the SQL workloads into the NoSQL version that can be used by Snowflake. We can configure the size of our workloads because Snowflake gives us control over the use of resources and costs.

The most valuable feature of Snowflake is it's an all-in-one data warehousing solution. 

The solution is very easy to use.

The product is very stable and flexible. The performance is good.

The product is quite scalable.

The solution is very fast. It's not clunky or slow.

The product, overall, is quite inexpensive. It's very cheap to use.

The solution is extremely user-friendly and easy to navigate. The user experience is very good.

The initial setup is pretty straightforward. It's simple.

We found that the initial setup was pretty easy.

The solution has been stable and has provided good overall performance.

A company can easily scale the solution. It's not too difficult to pull off.

The technical support on offer is excellent. They're helpful for the most part.

The Time Travel feature is helpful for accessing historical data and the ability to clone external tables is useful.

Once you have finished your designs they can be easily imported to Snowflake and the information can be readily accessed without an IT expert.

The overall ecosystem was easy to manage. Given that we weren't a very highly technical group, it was preferable to other things we looked at because it could do all of the cloud tunings. It can tune your data warehouse to an appropriate size for controlled billing, resume and sleep functions, and all such things. It was much more simple than doing native Azure or AWS development. 

It was stable, and their support was also perfect. It was also very easy to deploy. It was one of those rare times where they did exactly what they said they could do.

Snowflake is the latest technology. It has great flexibility whenever we are loading data and performs ELT (extract, load, transform) techniques instead of ETL.

This solution automatically performs micro-partitioning when the data is loaded. This creates a dynamic partition and based on the cluster, the performance is fast and really impressive.

Snowflake is using MPP, massively parallel processing techniques, which is a great feature. It saves developers time and allows us to focus more on client requirements.

The thing I find most valuable is that scalability, space storage, and computing power is separate. When you scale up, it is live from one second to the next — constantly available as you scale — so there is no downtime or interruption of services.

It has something like a time machine, as it is from Apple it incorporates that feature in a way similar to their operating system. So whenever you need a version of the data to test with, you can just go back and take a copy of what was backed up yesterday. It makes some things very easy. It backs up your data warehouses, so for example in our case, a colleague deleted a complete database and we just need to do an undrop on the database and the data was there again.

This helps you to have a development environment with current data. You can just clone your production environment and you have a development environment. Everything you do you can test it on real production data without destroying the production data itself.

These are significant advantages.

The data warehouse is one of the great concepts of Snowflake. The coding plans are also a great feature. You can switch out the values or sizes. 

Data Science capabilities are the most valuable feature.

The product offers a lot of great features.

Architectural-wise, it's got great architecture. That's what we are looking for. It's kind of decoupled from storage and has virtual warehouses. We like that we can travel and keep things virtual. For us, the virtual warehousing is likely the most valuable aspect. You can spin up as many virtual warehouses that you want. That's quite useful as a feature.

The solution offers everything you'd find on Azure or AWS. It has a lot of industry-standard features and capabilities.

The product has excellent autoscaling. We can actually compute and scale-out at the same time without having to depend on other tools. You can do it on the fly, or within queries, etc.

The Visual Copy Cloning is definitely one feature that everyone looks forward to due to the fact that it gives you regular backups. 

The solution offers a very good time travel function that allows you to travel back in time to before your systems we corrupted. You can go back into your history and grab the last backup before corruption so that you regain almost everything you need. It gives you 90 days to fetch the data back if you need to. It's better than Azure options.

The most valuable feature of Snowflake is the Mbps they have established because it's quite a bit faster than any other data warehouse. The solution has different warehouse sizes in place, and we're able to switch through and choose what we want. It can be done in one or two seconds. In other data warehouses, it may take around one minute to set up a different configuration. In Snowflake, it can be done in, two or three seconds. And apart from that, the most important thing given that I have to analyze all this, is that it's very good with the time travel, it's a great feature. 

All the people who are working with Snowflake are extremely happy with it because it is designed from a data-warehousing point of view, not the other way around. You have a database and then you tweak it and then it becomes a data warehouse. 

It has very nice features, such as snapshots, marketplace, and it is very easy to receive data-warehouse specifications.

The most valuable features are sharing data, Time Travel, Zero Copy Cloning, performance, and speed.

The solution is very easy to run the queries. We have a built-in query optimizer in Snowflake that works very well.

The solution's most valuable aspect is the ability to process the bulk amount of data and try to clone the database. We try to clone the production database. Instead of syncing the whole database, we can just clone it up and start working on it. Basically, the cloning and the database are very user-friendly.

The solution is very stable.

It's very easy to use, easy to query, and it provides pretty accurate results. It's a market leader. 

The most valuable features are:

1. The Virtual Warehouse and separate storage is definitely one of the best features. It automatically scales the warehouse up and down as per the usage.
2. Processing semi-structured data like JSON and XML has helped reduce a lot of coding that was needed earlier.
3. The speed of execution is definitely good.
4. There is zero maintenance activity required from users on the database, which is a big plus.
5. Working with Parquet files is supported out of the box and it makes large dataset processing much easier.
6. Automatic scaling up and down.

As it is SQL-like, it is easy to write queries.

The querying speed is fast.

The solution's most valuable feature is path application.

Its performance is most valuable. As compared to SQL Server, we are able to see a significant improvement in performance with Snowflake. 

The ETL and data ingestion capabilities are better in this solution as compared to SQL Server. SQL Server doesn't do much data ingestion, but Snowflake can do it quite conveniently.

Its performance is a big advantage. When you run a query, its performance is very good.

The inbound and outbound share features are also very useful for sharing a particular database. By using these features, you can allow others to access the Snowflake database and query it, which is another advantage of this solution. 

It has good security, and we can easily integrate it. We can connect it with multiple source systems.

Snowflake is a database, and it is very good and useful. The most interesting part is that memory management is very good in Snowflake. For a business intelligence project, SQL Server is taking a lot of time for reporting services. There are a lot of calculations, and the reporting time is shown as two minutes, whereas Snowflake is taking just two seconds for the same reporting services.

• I like the idea that you can assign roles and responsibilities, limiting access to data. That has been very interesting to us. 
• The robustness of the system is very useful to us. 
• The availability of the system. 

I have found the solution's most valuable features to be storage, flexibility, ease of use, and security.

The features that I have found most valuable are the ease of use, the rapidness, how quickly the solution can be implemented, and of course that it's been very easy to move from the on-premise world to the Cloud world because Snowflake is based on SQL also.

The syntax is advanced which reduces the time to write code. 

The most valuable feature is the snapshot database. In one second, you can just take a snapshot of the database for test purposes.

The scalability of this product is great and the fact that it has a so-called zero clone copy and is near zero maintenance is also great. There are a lot of good features, it's a very sophisticated, cutting edge technology and is super easy to use. They are developing the platform very, very quickly so there are plenty of new features implemented all the time. You can concentrate on implementing things in Snowflake without tuning or configuring it.

• Scalability. This solution has the ability to load a huge number of datasets (I have experience with petabytes of data) and process them. Storage is not limited, and we can increase what we want.
  
• Performance. The distributed architecture of Snowflake has the capacity to process huge datasets faster and allows us to scale up and down according to our needs.
• Flexibility. This feature is helpful for the user to increase the node size and config depending on their need. There is no need to wait for hardware to be in place whenever we increase the dataset. Snowflake provides the option to increase the node or cluster size whenever required.
• Multi-formatted accessibility. The Snowflake engine has the capability to read the following file formats: CSV, DELIMITER, FIXEDWIDTH, AVRO, JSON, BZIP2, GZIP, LZOP. The user can choose which format is best for their requirements.
• Configuration. Even though its running in the AWS platform, it beats their platform product. I feel more flexible with this solution than I do with Redshift.
• Snowpipe. Snowpipe is a better system to feed stream data to the Snowflake database.
  

Its speed and performance were the most valuable. Easy configuration of Snowflake in any cloud was also a benefit.

We find the data sharing and data marketplace aspects of Snowflake absolutely amazing.

The overall package is quite nice, and there is not one specific feature that I have found more valuable than the others.

The vendor is quite willing to implement requests for development, in particular for larger clients. It is a nice company to work with.

The architecture we'll be using due to being on the cloud will assure we have less to do. There will be no indexing, for example. Everything's managed by the servers. That way, we can focus on the data warehouse and on the data.

From a data warehouse perspective, it's an excellent all-round solution. It's very complete.

The entire managed service operations for the solution is great. Snowflake does everything for us. Whatever version they have, they implement the latest for us; we don't have to worry about any versions, any upgrades, anything else because they handle it.

I like the fact that we don't need a DBA. It automatically scales stuff.

Snowflake has better performance features; it automatically knows the difference between the data volume. It adjusts itself.

The performance is great. It internally optimizes well.

The product is stable.

The solution is scalable.

The use of micropartitions and metadata means that there is very little management needed and the user can focus purely on actually getting value out of their data. In addition, the cloning feature makes problem resolution and cutover extremely pain-free.

It is a cloud solution with many useful features. It has the data science capability. It can transform data and prepare data for a data science project with scalability.

It is a very well-distributed system. It has different data engines for different applications. Many applications can use different computational engines at the same time. In terms of data processing, the feeling was similar to working with a relational database but in a scalable way.

The relational piece and how one dimension relates to another just by using a key is the solution's most valuable aspect. We are managing everything by using simple relations. It's all about the relationships between dimensions.

The solution is very easy to understand. It's a simple solution. It's not complicated.

The product does a lot of wonderful stuff that a lot of these companies want to do without too much effort.

The initial setup is straightforward.

The pricing is reasonable and matches the rest of the market.

The solution is quite stable.

Our clients have not had any trouble scaling.

The most valuable features are: 

The multi-clustering: being able to access stored data without contention.

Virtual Warehouse (VW) sizing: Change the size of your VW on demand. 

Zero copy clone: Easy to create development and test environments.