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Snowflake Reviews & Product Details
Snowflake is a cloud-based data warehousing platform designed to efficiently store, process, and analyze large volumes of data. It stands out for its ability to scale computing and storage resources independently, allowing users to manage data and analytics workloads more flexibly. With its unique architecture, Snowflake facilitates seamless data sharing among users, enabling collaborative data-driven decision-making. It supports various data structures and types, including structured and semi-structured data, making it a versatile choice for organizations looking to harness the power of their data.
| Capabilities |
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|---|---|
| Ease of use |
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| Deployment | Cloud / SaaS / Web-Based |
| Support | 24/7 (Live rep), Chat, Email/Help Desk, FAQs/Forum, Knowledge Base, Phone Support |
| Training | Documentation |
| Languages | English |
Snowflake Pros and Cons
- Multi-cloud support across AWS, Azure, and Google Cloud
- Separation of compute and storage for scalable, on-demand analytics
- Native support for semi-structured data formats like JSON and Avro
- Secure data sharing without moving or copying data
- Pay-per-second pricing model for cost optimization
- Advanced capabilities might be excessive for small businesses with limited data needs
- Potential for increased costs with high data storage and compute usage
- Learning curve for users unfamiliar with cloud-based data platforms
- Dependence on internet connectivity for accessing the platform
- Limited offline capabilities
Very fast onboarding - very proactive Sales/Technical account assistance
Somewhat lack of technical tools to load data in Snowflake. Community is still somewhat young
Analyzing large amounts of consumption SVOD data. Able to run really quick queries and build large data backends for our Tableau reports
first: the fast compute and unlimited storage . second: the connection to AWS S3. third the snow piple.
Query GUI, it will be nice to have all the features like the generic query analyzer , example: DB VISUAL
Big data for analytics Connection to AWS S3
Probably my favorite thing is how we can spin up the size of Snowflake for our ETL loads and derived tables builds throughout the day.
I think what we struggle the most with is applying security roles to all schemas, databases and tables. Snowflake does have robust security but it does take some time to set up.
We are able to get our important reports out much sooner each day than when we are on Redshift.
Ease of use, scalability and excellent support
Nothing I really dislike about it, great platform
Big data analytics to service the lifesciences market
The easy to increase performance power, the separation of database and warehouse.
The setup process of snowpipe because it is not easy and confusion. I like copy command setting up process, it is straightforward and easy to maintain
The SQL Server cannot handle of amount of financial data we have to process on regular basis.
It is super easy for my work as a Data Engineer to connect to Snowflake via Spark and streamline our ETL pipeline. It is ANSI SQL-compliant, so it is not much new to learn for anyone who has a SQL background.
I wish it supported Dynamic SQL. And, while it is convenient that UDFs can be written in JavaScript, I would love to see the addition of more languages.
We are able to store and easily query more data than ever before.
The snapshot capabilities. The ability to take snapshots quickly so that we can work with a copy of the data
The security model can be a bit tedious.
Snowflake is helping us to scale our data business in a cost efficient manner.
No maintenance required, good query performance, good SQL support and features, super easy to scale, reliable so far. Data cloning and sharing is unique and awesome and fits our use case perfectly.
Some bugs in the Python connector, some query errors for complex queries, can get pricy if high concurrency is required. Permission management differs from MySQL. We only had a single service outage so far.
We are building a data warehouse on Snowflake, we have eliminated database maintenance costs and greatly reduced TCO. Query performance has greatly improved.
We got to modernise our ailing, ageing data infrastructure without it costing the earth. Our data staff, all conversant in SQL were able to transfer their skills overnight, and our analytics staff all got access to cloud scalability to support their heavy analytical workloads (no Hadoop in sight). VERY, VERY cost effective way to modernise!
Nothing - it's brilliant! Would really love there to be a built-in environment for scheduling SQL scripts, but there are plenty of ETL tools for this already.
Business problems / opportunities = Single Customer View. Customer Data Platform. Website engagement / data collection. Enterprise Data Warehouse. Business Intelligence modernisation. Predictive Analytics. Benefits = cost savings over "big data" solutions; cost saving on data warehouse management, business intelligence modernisation, supporting predictive analytics initiatives that are saving money / boosting top line sales. In-sourced single customer view.
The database is incredibly fast even when using many joins and even with text joins. The functions ROLLUP and CUBE are critical to the way we use Snowflake and those have been unavailable in other systems. Our sales rep Sarah at Snowflake has been wonderful to work with.
Support has been working a bug where queries return incorrect results for a while now. This does affect our customers, but the incorrect results cause rows to be shown many times so it's more annoying than it is misinformative. Snowflakes ABSOLUTE REFUSAL to shutdown while overloading it is awesome, but it has caused service interruption on our side due to a bad query hogging all of the resources. Instead of quitting and restarting all processes, Snowflake dutifully worked on churning the data. Good? Bad? I don't know. The query was never going to happen, so we ended up manually having to kill it so all other backed up queries could run. That being said, we are still working on developing our skills with using all of the database tools.
We use snowflake for the back end of our reporting engine. Midday we will see huge spikes in reporting load and the auto scaling capabilities allow us to get the most out of our money by spinning up more only when it's needed.