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Snowflake offers superior scalability, flexibility, and cost-efficiency for cloud-native analytics. Whereas, Oracle excels in complex transactional workloads and on-premise environments but lacks Snowflake’s cloud-native agility.
In today’s article we learn about two major Data Warehouse solutions available in the market, their key features, key differences etc.
Large amounts of data are generated by organizations and its people. The organizations are always struggling to find a way to derive a meaningful outcome from tons and tons of data which is taking up a lot of space and lying but of no use to the enterprises.
DBMS or database management systems could store large volumes of data in tables for the purpose of segregation but what about deriving meaningful insight from that data? There Data Warehouse systems come into the play which store large amounts of data and produce meaningful statistical results which may help organizations in decision making.
What is Snowflake
Snowflake is a Data Warehouse especially designed for cloud. It helps in centralization of data from multiple sources and enable to run in-depth business insights. Snowflake is designed to handle structured and semi-structured data from multiple sources which allows integration and analysis of data from diverse systems.
- Snowflake has unique compute architecture separating compute and storage which enable users to scale each of them independently based on the need.
- The elasticity ensures optimal allocation of resources and cost savings as users only pay for actual compute and storage being utilized.
- Snowflake uses SQL based query language having an intuitive interface with robust security and compliance to ensure data privacy and data protection.
- It can handle large volumes of concurrent workloads without impacting the performance.
- Auto scaling adjusts resources as per demand.
- It supports native integration with Apache Spark, Python and R.
What is Oracle
Oracle is available in both flavors as cloud data warehouse and on premises data warehouse. Oracle provides centralized location for data analytics activities. It is a robust database and highly scalable relational management system.
- It supports a wide range of data types and provides advanced features such as modelling data, data indexing and data query.
- Oracle provides a complete ecosystem of data management tools with a high performance, optimized platform for data warehousing.
- It has self-service capabilities for performing analytics, enabling users to explore and data visualization, building interactive dashboards and generate actionable insights.
Comparison: Snowflake vs Oracle
Below table summarizes the differences between the two data warehouse solutions:
| Features | Snowflake | Oracle |
|---|---|---|
| Solution | Snowflake is only available as cloud-based solution | Oracle comes into two flavors – cloud based and on premises |
| Data handling | Snowflake automatically optimize queries for performance | Oracle requires manual fine tuning for queries |
| Ease of use | Snowflake automatically applies – patches, upgrades and security fixes to reduce management workload | Oracle requires a database administrator to manage patching, upgrades and other such tasks |
| Management | Snowflake supports auto management of database indexing, partitioning and other data management tasks | Oracle requires a database administrator to manage any scalability related tasks |
| Features | Separate investment is required having standalone machine learning platform to execute algorithms as it does not support this capability out of the box. | Oracle let you built and run machine learning algorithms inside the data warehouse |
| Data security | Snowflake uses a multi-layered approach towards security such as data encryption, role-based access control and auditing. | Oracle provides features such as data encryption, fine grained access control, and monitoring. |
| High availability and disaster recovery | Data replication to three data centres and auto failover at no additional cost. Cross cloud and region data replication for disaster recovery | Real application clusters (RAC) with a standby database. Needs additional hardware for standby. |
| Data compression | Automatic data compression. compression around 3 to 6 times of raw data | Manual data compression based on indexes and database keys |
Download the comparison table: Snowflake vs Oracle
Quick tip!
- Snowflake has 21.50% market share in the data warehousing market.
- Oracle has 9.89% market share in the data warehousing market.