Q) What is a Snowflake cloud data warehouse?
Ans. Snowflake is an analytic data warehouse implemented as a SaaS service. It is built on a new SQL database engine with a unique architecture built for the cloud. This cloud-based data warehouse solution was first available on AWS as software to load and analyze massive volumes of data. The most remarkable feature of Snowflake is its ability to spin up any number of virtual warehouses, that means the user can operate an unlimited number of independent workloads against the same data without any risk of contention.
Q) What is Unique about Snowflake Cloud Data Warehouse?
Ans. Snowflake is cloud native (built for the cloud).So, It takes advantage of all the good things about the cloud and brings exciting new features like,
- Auto scaling
- Zero copy cloning
- Dedicated virtual warehouses
- Time travel
- Military grade encryption and security
- Robust data protection features
Snowflake is a poetry. It’s beautifully crafted with smart defaults –
- All the data is compressed by default
- All the data is encrypted
- Its Columnar, thereby making the column level analytical operations a lot faster
Not to mention the number of innovations in the product – eg. Intelligent Services layer, data shares, tasks & streams. Snowflake also has a simple and transparent pricing, which makes it very easier even for smaller businesses to afford a cloud datawarehouse
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Q) How is data stored in Snowflake?
Ans. Snowflakes store the data in multiple micro partitions which are internally optimized and compressed. The data is stored in a columnar format in the cloud storage of Snowflake. The data objects stored by Snowflake cannot be accessed or visible to the users. By running SQL query operations on Snowflake, you can access them.
Q4) What type of database is Snowflake?
Ans. Snowflake is built entirely on a SQL database. It’s a columnar-stored relational database that works well with Excel, Tableau, and many other tools. Snowflake contains its query tool, supports multi-statement transactions, role-based security, etc., which are expected in a SQL database.
Q) What is a Columnar database and what are its benefits?
Ans. Columnar databases organize data at Column level instead of the conventional row level. All Column level operations will be much faster and consume less resources when compared to a row level relational database
Q) What are the different ways to access the Snowflake Cloud Datawarehouse?
Ans. You can access the Snowflake Data Warehouse using
- Web User Interface
- ODBC Drivers
- JDBC Drivers
- SnowSQL Command line Client
- Python Libraries
Q) Can AWS glue connect to Snowflake?
Ans. Definitely. AWS glue presents a comprehensive managed environment that easily connects with Snowflake as data warehouse service. These two solutions collectively enable you to handle data ingestion and transformation with more ease and flexibility.
Q) Explain Snowflake editions.
Ans. Snowflake offers multiple editions depending on your usage requirements.
- Standard edition – Its introductory level offering provides unlimited access to Snowflake’s standard features.
- Enterprise edition – Along with Standard edition features and services, offers additional features required for the large-scale enterprises.
- Business-critical edition – Also, called Enterprise for Sensitive Data (ESD). It offers high-level data protection for sensitive data to organization needs.
- Virtual Private Snowflake (VPS) – Provides high-level security for organizations dealing with financial activities.
Q) What is Snowflake Caching?
Ans. Imagine executing a query that takes 10 minutes to complete. Now if you re-run the same query later in the day while the underlying data hasn’t changed, you are essentially doing again the same work and wasting resources
Instead Snowflake caches the results of every query you ran and when a new query is submitted, it checks previously executed queries and if a matching query exists and the results are still cached, it uses the cached result set instead of executing the query. This can greatly reduce query times because Snowflake retrieves the result directly from the cache.
Q) Define the Snowflake Cluster.
Ans. In Snowflake, data partitioning is called clustering, that specifies cluster keys on the table. The method by which you manage clustered data in a table is called re-clustering.
Q) Explain Snowflake architecture.
Ans. Snowflake is built on a patented, multi-cluster, shared data architecture created for the cloud. Snowflake architecture is comprised of storage, compute, and services layers that are logically integrated but scale infinitely and independent from one another. Snowflake is built on AWS/Azure/GCP cloud data warehouse and is truly Saas offering. There is no software, hardware, ongoing maintenance, tuning, etc. needed to work with Snowflake.
Three main layers make the Snowflake architecture – database storage, query processing, and cloud services.
- Data storage – In Snowflake, the stored data is reorganized into its internal optimized, columnar, and optimized format.
- Query processing – Virtual warehouses process the queries in Snowflake.
- Cloud services – This layer coordinates and handles all activities across the Snowflake. It provides the best results for Authentication, Metadata management, Infrastructure management, Access control, and Query parsing.
Q) What are the features of Snowflake?
Ans. Unique features of the Snowflake data warehouse are listed below:
- Database and Object Closing
- Support for XML
- External tables
- Hive metastore integration
- Supports geospatial data
- Security and data protection
- Data sharing
- Search optimization service
- Table streams on external tables and shared tables
- Result Caching
Q) What is Time Travel in Snowflake?
Ans. Time travel is a cool feature which lets you access data as of any time in the past. For example, if you have an Employee table and if you delete the table accidentally you can use time travel and go back 5 minutes and retrieve the data back. Snowflake Time Travel enables accessing historical data (i.e., data that has been changed or deleted) at any point within a defined period. It serves as a powerful tool for performing the following tasks:
- Query data in the past that has since been updated or deleted
- Create clones of entire tables, schemas, and databases at or before specific points in the past
- Restore tables, schemas, and databases that have been dropped
Q) Tell me something about Snowflake AWS?
Ans. For managing today’s data analytics, companies rely on a data platform which offers rapid deployment, compelling performance, and on-demand scalability. Snowflake on the AWS platform serves as a SQL data warehouse, which makes modern data warehousing effective, manageable, and accessible to all data users. It enables the data-driven enterprise with secure data sharing, elasticity and per-second pricing.
Q) Describe Snowflake computing.
Ans. Snowflake cloud data warehouse platform provides instant, secure, and governed access to the entire data network and a core architecture to enable various types of data workloads, including a single platform for developing modern data applications.
Q) What is the schema in Snowflake?
Ans. Schemas and databases used for organizing data stored in the Snowflake. A schema is a logical grouping of database objects such as tables, views, etc. The benefits of using Snowflake schemas are it provides structured data and uses small disk space.
Q) What kind of SQL does Snowflake use?
Ans. Snowflake supports the most common standardized version of SQL, i.e., ANSI for powerful relational database querying.
Q) What are the cloud platforms currently supported by Snowflake?
- Amazon Web Services (AWS)
- Google Cloud Platform (GCP)
- Microsoft Azure (Azure)
Q) What ETL tools do you use with Snowflake?
Ans. Following are the best ETL tools for Snowflake:
- Hevo Data
- Apache Airflow