Snowflake and Looker are both well-known tools for business intelligence (BI), data analytics, and data management. Companies need these data solutions a lot because they want to use the huge amounts of data they have. Instead of a small team of data scientists slicing and dicing data, teams from management, marketing, sales, and IT are now using big data in their daily work.
Users sometimes have to choose between Snowflake and Looker, which are both well-known data management and analytics systems. Each data option has pros and cons that can be made. Both give business intelligence apps the volume, speed, and quality they need. But they are the same in as many ways as they are different. They look at the data field in different ways. So, the choice usually comes down to how much the organization likes the data platform and how well it fits with the organization’s big data plan.
Looker vs Snowflake Comparison table
In the table comparing Looker and Snowflake, their different jobs are shown: Looker is great at data analytics, visualizing data, and making it easy for people who aren’t tech-savvy to use. Snowflake, on the other hand, focuses on strong data warehousing, processing, and scalability to meet the needs of data workers and enterprise-level data needs.
|Type of Tool||Business Intelligence and Analytics||Cloud Data Warehousing|
|Purpose||Data exploration, visualization, and reporting||Data storage, processing, and querying|
|Integration||Integrates with various data sources, databases, and platforms||Data integration and warehousing tools|
|Data Source Connectivity||Connects to multiple data sources, including databases, APIs, and flat files||Supports various data sources, including on-premises and cloud-based|
|Querying||Uses LookML for modeling and SQL for querying||Supports ANSI SQL for querying data|
|Scalability||Scales well for business intelligence and analytics needs||Provides elastic scalability for data storage and processing|
|Data Processing||Limited data transformation capabilities||Offers extensive data transformation and processing options|
|Security||Provides role-based access control and encryption||Offers robust security features, including encryption and access control|
|Community/Support||Active user community with various resources||Offers customer support and documentation|
|Notable Clients||Yahoo, Spotify, IBM, Kickstarter||Netflix, DoorDash, Capital One, Adobe|
|Deployment||On-premises or cloud deployment options||Cloud-based deployment|
|Visit Website||Visit Website|
Looker vs Snowflake: Ease of Use and User Interface
When comparing Looker and Snowflake, the ease of use and user experience are very important. Looker has a simple, easy-to-use interface that makes it easy for anyone to create and adjust reports and dashboards, even if they don’t know much about technology. Its drag-and-drop feature and variety of themes and pre-built visualizations make it easier to explore data and see what it looks like. Also, Looker’s data modeling features make data modeling less complicated, which makes it easier for more people to use.
Snowflake, on the other hand, also has an easy-to-use interface, especially in its cloud-based setting. Its web-based console is well-organized and makes it easy for users to run queries and handle data warehouses. Many data workers are already familiar with SQL, which makes Snowflake easier to learn. But it’s important to note that Snowflake’s main focus is on data warehousing and storage. It has simple data visualization tools, but it may not have as many features as Looker when it comes to making complex, interactive dashboards.
Looker vs Snowflake: Data Integration and Storage
Integration and storage of data are important parts of any current business intelligence and data analytics platform. Both Looker and Snowflake are great at these things on their own. Looker is best known for its ability to visualize and analyze data, but it also works well with many different data sources. It lets users connect to various databases, cloud data warehouses, and applications. This makes it a good choice for businesses with a lot of different kinds of data.
On the other hand, Snowflake is good at storing info in the cloud. It gives you a way to store data that is scalable, adjustable, and fast, and it can handle large amounts of data well. Snowflake’s design separates storage from computation, so users can scale storage without affecting computation, which helps keep costs down. It also works with both semi-structured and structured data, which makes it a good choice for both data lakes and data warehouses.
Data Analytics and Visualization Tools
Data analytics and visualization tools are important parts of both Looker and Snowflake. These tools help businesses get useful information from their data. Looker has a full set of tools for exploring and displaying data, making it easy for users to make dynamic dashboards and reports. Its easy-to-use interface lets non-technical users do ad-hoc analysis, and its strong modeling layer makes sure that data is accurate and consistent.
Snowflake is mostly a cloud-based data warehouse platform, but it also works well with a number of tools for analytics and data display. Users can connect to Snowflake data with well-known BI tools like Tableau, Power BI, and Looker. This gives organizations the freedom to choose the analytics and visualization tool that best fits their needs and tastes. This makes sure that data analysis is done in a way that is best for them.
Looker vs Snowflake: Performance and Scalability
When comparing Looker and Snowflake, performance and flexibility are the most important things to look at. Looker is mostly a tool for data analytics and visualization, but it also does a good job of making interactive dashboards and giving insights. Its speed is mostly determined by the database or data warehouse it is built on, and it can handle moderately-sized datasets well.
Snowflake, on the other hand, is a cloud-based data warehouse tool that shines when it comes to scalability and performance because its architecture is built for data-intensive workloads. Snowflake’s unique multi-cluster, shared-data design lets it grow horizontally, keeping performance high even as the amount of data increases. It is great at handling big and complicated datasets, and it can easily handle multiple users and queries at the same time without slowing down.
Looker vs Snowflake: Data Security and Compliance
When comparing Looker and Snowflake, data protection and compliance are the most important things to think about. Looker is a platform for analyzing and displaying data. It relies on the security methods of the data sources it uses. It has role-based access control, which lets administrators set and enforce permissions to view data. But it depends a lot on the security of the data storage and processing services it works with.
Snowflake, on the other hand, is a cloud-based data warehouse that puts a lot of focus on security. It has strong features like encryption at rest and in motion, multi-factor authentication, and access controls at the granular level. Snowflake’s design also keeps customer data separate, which makes the data safer. Snowflake also follows important compliance standards like SOC 2, HIPAA, and GDPR, which is important for companies that deal with private data.
Integration with Other Tools and Services
When considering Looker and Snowflake, it’s important to think about how well they work with other tools and services. Both systems know that a strong ecosystem is important to make them work better. Looker has a flexible integration system that makes it easy to connect to different data sources and tools from other companies. It is easy to connect to databases, cloud storage services, and business information tools that are already widely used. Also, Looker’s open API makes it easy to create custom integrations that meet the needs of each company.
On the other hand, Snowflake’s ability to work with other systems is also very amazing. Snowflake is a cloud-native data warehouse option that works well with AWS, Azure, and Google Cloud. This makes it a good choice for companies that have already invested in these ecosystems. It also has built-in connections to famous BI tools, which makes it easy to visualize and analyze data. Snowflake’s Data Marketplace gives users access to a wide variety of external data sources, which increases the number of ways it can be integrated.
Looker: Pros and Cons
- User-friendly interface.
- Self-service data exploration.
- Strong data visualization.
- Active user community.
- Limited data transformation.
- Not ideal for complex data processing.
Snowflake: Pros and Cons
- Powerful data warehousing.
- Scalable and elastic.
- Robust data processing.
- Advanced security features.
- Requires SQL expertise.
- Complex for non-technical users.
Looker vs Snowflake: which one should you consider?
Choose between Looker and Snowflake based on your goals and the infrastructure you already have. Looker may be a better choice if you want a powerful tool for analyzing and displaying data that can be easily connected to other programs. Its open API and flexible integration framework make it a good choice for companies that want a solution they can customize.
On the other hand, Snowflake is a great choice if you need a powerful cloud-native data warehouse tool that works well with major cloud providers. It is great at storing, processing, and scaling data, which makes it perfect for businesses that need to store and process a lot of data and have cloud-based strategies.
Looker supports OAuth for connections to Snowflake. This means that each Looker user logs in to Snowflake and gives Looker permission to use their own Snowflake user account to run searches on the database.
Looker is a powerful business intelligence and data visualization tool that helps companies make charts and graphs that show what they are doing and help people understand it better.