Redshift vs snowflake – The Head on Head Comparison
Data warehouses turned out to be a lifeline for many businesses. It is a hub that stores all kinds of data in a bulk volume. The most fundamental benefit of data warehouse is to reap prolific insights from historical and real-time data to take business decisions and to introspect the current scenarios with analytics. However, selecting the right data warehouse solution is indispensable for any organization to join the race in the highly competitive business world. AWS Redshift and Snowflake are the most popular services in the cloud world. let’s compare these two from head to toe.
AWS RedShift – The Quick View
AWS Redshift is a Dataware house service launched by Amazon. It is designed to handle tremendous volume of data up to exabytes (10^18 bytes) at a super speed. It can process different kinds of data like structured data, unstructured data and semi structured data. This service is an ideal option for Enterprise Datawarehouse. Secuity is no more a threat when you adopt AWS redshift as it offers Data encryption at rest.
What Makes AWS Redshift a one in a million?
Ideally, we can highlight two things here, Massive Parallel Processing (MPP) and it is suitable for Online Analytical Processing (OLAP). These two technologies made AWS redshift stand out in the crowd.
OLAP is column-oriented, with regular SQL queries, one can fetch the data with redshift. Massive parallel processing is responsible for delivering the result for queries at lighting speed.
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Snowflake – The overview
Snowflake tags themselves as a true self-managed service. There would be no need to install any hardware or software.
Snowflake offers a variety of features, including automatic query optimization, support for both structured and semi-structured data, and integrations with popular BI and ETL tools. The platform has gained popularity among organizations of all sizes, from startups to large enterprises, due to its flexibility, ease of use, and cost-effectiveness.
What’s unique about Snowflake?
Snowflake’s unique architecture separates storage and compute, which allows users to scale resources independently based on their needs. Additionally, Snowflake’s built-in security features ensure that data is kept safe and compliant with various regulations, including HIPAA, GDPR, and PCI-DSS.
It does not support private clouds. It is also fortified with massive parallel processing to fetch information for queries
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Similarities between Snowflake and Redshift
AWS Redshift and Snowflake do have some similarities and dis similarities. Will look both here.
- Both incorporates Massive Parallel Processing (MPP)
- Both supports column-oriented databases
- SQL based query engines are used to access the data in Red Shift and SnowFlake.
- The fundamental use case of both is to retrieve useful insights for business.
AWS RedShift Vs Snowflake
Let’s compare these two based upon the metrics like performance, Maintenace, storage, security and cost
Performance
AWS redshift and snowflake incorporate MPP, Massive parallel processing to deliver queries. So, undoubtfully both have the potential to fetch the desired data at a super speed.
When it comes to Query optimization, Snowflake uses a technique called automatic query optimization to optimize query performance in real-time, which means that users don’t need to worry about tuning queries manually. In the case of AWS redshift, it requires manual tuning to optimize queries
Maintenance
When it comes to maintenance, Snowflake takes over the entire responsibility of maintaining things. Redshift automates some things like workload management, vacuuming yet it needs additional manual maintenance
Integration
Third party tool integrations are very important to extract fruitful insights. Both Redshift and showflakes support third-party integrations to get the most out of it.
Security
AWS Redshift provides end-to-end security with no extra charge and offers cluster encryption, SSL connections and VPC/VPN network isolation.
Snowflake provides VPC/VPN isolation, and it also impacts pricing.
Storage and Compute Separation
Snowflake separates storage and computing, allowing users to scale each independently. It uses a unique multi-cluster, shared data architecture that enables multiple users to access the same data simultaneously while ensuring data isolation and security.
On the other hand, Redshift is based on a cluster-based architecture where both storage and compute reside within the same cluster. which demands manual scaling process. Recently, it introduced R3 nodes to scale compute irrespective of the storage, thus it creates a very similar environment just like snowflake.
Supported Data Types
AWS redshift can easily handle Structured and some semi-structured data with integration with AWS S3, it can also handle unstructured data. Snowflake handles all kinds of data from the year 2021
Cost
Another significant difference between Snowflake and Redshift is their pricing model. Snowflake offers a consumption-based pricing model, where users pay only for the storage and compute resources they use. This model is flexible and cost-effective, allowing users to scale resources up or down as needed.
Redshift, on the other hand, offers a more traditional pricing model where users pay for the size of the cluster they use, regardless of whether they use all the resources or not. This means that users may end up paying for unused resources, which can be expensive.
Amazon Redshift Monthly Cost = [Price Per Hour] x [Cluster Size] x [Hours per Month]Â
Which one is the best?
“Which is the best ” is the obvious question. but I don’t have an answer for this. Both have their own features and functionalities for their users.
The selection should be entirely dependent upon your business goals, budget, compliances, security, etc. Compare the features and map it out which one fits well for business needs.
Conclusion
Both Snowflake and Redshift are good in their own ways. Yet, to survive in this competitive business both need to groom themselves up to provide enhanced services. I may sound diplomatic but the choice between the two will depend on the specific business needs and the workload you are dealing with.
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