15 Leading Snowflake Competitors Delivering The Data Cloud

In the world of Big Data, having a data warehouse setup is costly and cumbersome. One such cloud platform that offers Big Data as a Service and reduces the need for separate data warehouses, data lakes, and data marts is Snowflake.

Snowflake has been highly popular in the business scenario with respect to cloud-based data management. As one of the leading technologies in the data warehousing arena, Snowflake includes a data warehouse as a service with innovative features.

Just the way Snowflake has been capturing the liking of all, there are other Snowflake competitors that have been capable of offering a similar array of services. Before we explore who are these Snowflake competitors, let us have a fleeting glance at what Snowflake is and its salient features.

What Is Snowflake?

Snowflake Data Cloud enables the most critical workloads since it is one platform, with many workloads with no data silos. It creates data-intensive applications and is trusted by organizations worldwide. It provides accurate and fast availability of data through a uniform source.

It offers seamless integration with other BI and data integration tools like Tableau, Sigma, Qlik, etc. It works effectively on Google Cloud Platform, Azure, and Amazon S3. It reduces the administration needs of conventional warehousing solutions and needs no infrastructure to be managed.

It has an exceptional business model offering cloud-based data warehousing and storage services. It creates data-based business insights, a modernized data platform with continuous data collaboration. As a fully managed service, it is easy to use and can handle multiple concurrent workloads.

Snowflake Features:

• Scalable, secure, reliable, fast, and concurrent
• Almost zero management
• Flexible and easy to use
• Data import, export, sharing
• Database replication and failover
• Option to choose either ETL or ELT
• Robust customer and community support
• Brand recognition and customizable product offering

Companies Using Snowflake:

• Amazon
• Google
• Microsoft
• Capital One
• Warner Music Group
• jetBlue
• DoorDash
• Allianz
• Frontify
• Autodesk
• Disney Ad Sales
• Pizza Hut
• Flex
• Billie

As we wonder who the Snowflake competitors are, let us explore the list of Snowflake Alternatives that are offering tough competition to Snowflake.

Top Snowflake Competitors Offering Optimum Services

• Amazon Web Services (AWS)
• Cloudera
• Google Cloud Platform
• Microsoft Azure
• Teradata
• Oracle
• Databricks
• Panoply
• Redshift
• Google BigQuery
• PostgreSQL
• IBM
• Apache Druid
• Dremio
• Vertica

Amazon Web Services (AWS):

Powered by Amazon, AWS has been recognized to be a highly flexible, reliable, cost-driven, and comprehensive platform to provide ultimate class app performance and for hosting your IT infrastructure on the Internet.

AWS, as a cloud-based platform, is meant to facilitate app providers and vendors in hosting applications with speed and security. It offers on-demand computing resources that don’t need users for setting up of local servers.

Salient Features:

• Flexible, robust, and scalable
• Easy to learn and sign-in procedure
• Integration with Amazon services like AWS Lambda etc.
• Encompasses IaaS, PaaS, and SaaS
• Provides on-demand processes like computer power etc.

Cloudera:

Cloudera is a known Snowflake competitor that offers enterprise data cloud services. It has a hybrid data platform that converts complicated data into understandable insights through secure data management.

Users can easily and quickly perform data analytics, tracking and securing it thoroughly. Powered by Hadoop, it supports Big Data management with appropriate data storage and management. There are self-service tools for data analysis.

Salient Features:

• Real-time data analytics
• Operational database
• Easy and fast data management
• Hybrid development
• Data Science and ML

Google Cloud Platform:

Powered by Google, Google Cloud Platform is a known name for cloud computing services that offer IaaS, PaaS, and serverless computing. The Google App Engine is a platform to develop and host web apps in Google-managed data centres.

This tool offers a web-based GUI that can be leveraged for the management of Google Cloud projects. It includes a range of hosted services for computing and storing applications. These services can be availed by developers, administrators, and IT people through the network.

Salient Features:

• Access to resources from anywhere
• An automatic environment with web tools
• On-demand accessibility of computing resources
• Data storage and computing
• Reliable, relevant, and secure

Microsoft Azure:

Microsoft Azure is a flexible cloud computing platform that hosts content on the cloud servers with great effectiveness. It offers a wide range of services that utilize the potential of PaaS, SaaS, and IaaS with support from other languages and frameworks.

It has offerings like Azure Data Lake Store, Azure Synapse Analytics that act as good competitors to Snowflake. It offers application management through Microsoft-managed data centres.

Salient Features:

• Scalable, elastic with strong dashboard support
• Seamless third-party integration support
• Support for DevOps and CI
• Integrated Cloud setup
• Close integration with other Microsoft tools

Teradata:

Teradata is a leading, multi-cloud platform that helps in analyzing enterprise-level data from different sources. It offers cloud-based products, business analytics, and consulting. It deals with database analytics software subscriptions.

Teradata offers versatile database features and possesses a large user base. It is ideal for data warehousing and mining. It has a strong partner network and supports hybrid multi-cloud services.

Salient Features:

• Unified data source
• Cloud-based and on-premises data warehousing
• Business modelling
• Scalable, mature, and reliable
• Modernized data analytics

Oracle:

Oracle is a known name in the world of databases and technology for years. It offers a range of products like Oracle Database, Oracle Cloud etc. that can pose as a competitor to Snowflake.

It is popular for creating database software, enterprise software, cloud-based systems etc. for large-sized clientele, all around the globe. As a database management software, it offers cloud computing solutions via PaaS, IaaS, and SaaS models.

Salient Features:

• Cross-platform support
• Easy exchange of information through the flexible network stack
• ACID compliance, reliable with data integrity
• Portable, fast, secure, and efficient
• Multiple database management

Databricks:

Databricks is often compared to Snowflake as it blends the best of data warehouses and data lakes into a data lake house architecture. It teams up on all your data, analytics, and AI workloads. It creates a web-based platform with automatic cluster management.

Databricks comes from the creators of Apache Spark, and it performs data science and engineering all around the Machine Learning systems, beginning from preparing data to experimentation and controlling configurations.

Key Features:

• Integrated identity management
• Interactive workspace
• Wide range of data sources
• Optimized Apache Spark environment
• Auditing and secure deployment

Panoply:

Panoply is a leading data warehousing tool also known for its ETL capabilities. It combines an effective data warehouse with no-code data integration. It offers great integration with other third-party tools and hence is considered effective in terms of cost.

As a comprehensive cloud data warehouse service, it offers its users the facility to directly query from the platform or have a connection to the respective tool. Its inbuilt ETL facilities connect well with different data sources.

Key Features:

• Zero maintenance
• Plug and play compatibility with BI tools
• Pre-designed SQL queries
• Automated data type detection
• Handsfree scaling

Redshift:

Powered by Amazon, Redshift is a cloud-driven, Big Data warehousing solution that makes use of SQL for analyzing data. Data could be in different formats – structured or unstructured across different databases, warehouses, or data lakes.

Redshift is apt for data scientists and data engineers for managing large-scale datasets and database migrations. It makes use of third-party tools for data transformation and ETL jobs. It complies well with the HIPAA and GDPR rules and regulations.

Key Features:

• Fully managed cloud-based data warehouse
• Powerful and good performance
• The idea for data scientists and engineers
• Easy for deployment and management
• Cost-effective and scalable

Google BigQuery:

Powered by Google, BigQuery is a multi-cloud data warehouse that is agile and scalable. It is a completely managed and serverless data warehouse. It follows the PaaS model supporting queries through ANSI SQL.

It empowers the analysis of petabytes of data and possesses inbuilt machine learning competencies. It assists organizations to execute business analytics with scalability. It integrates well with other Google products like Google Analytics.

Key Features:

• Geospatial analysis
• Affordable and flexible storage capabilities
• Complete support from the Google Cloud Platform
• Seamless integration with machine learning tools
• Database scalability and automatic backups

PostgreSQL:

Postgres is a popular, free, open-source RDBMS that is extensible and SQL compliant. It is appreciated by developers since it is highly reliable, stable, and performs well. There is a huge community support from the Postgres community.

It is utilized as the main data store for multiple geospatial, web, and mobile applications. It offers fewer maintenance costs than its peers but will require an ETL tool for getting the data into storage units.

Key Features:

• Large data integrity and data capacity
• Table inheritance
• Multi-version concurrency control
• Diverse replication and indexing methods
• Open-source RDBMS

IBM:

IBM is a leading multinational that offers services in the areas of technology services, cognitive services, cloud platforms, etc. IBM DB2 has been offering data warehousing and hosting services in the areas of the data warehouse.

There is total control over data and applications that is manageable and effective. It offers an in-memory BLU processing technique with high performance and scalability. The infrastructure is quite robust and offers in-database analytics.

Key Features:

• MPP architecture
• Ideal for hybrid architecture
• Faster querying capabilities
• Optimized storage and SQL compatibility
• Enhanced performance with AI

Apache Druid:

Apache Druid is an open-source, real-time, cloud-native, distributed data store that is written in Java. It is meant to create modernized and fast data analytics applications by consuming huge quantities of data and offering queries.

It is free to use and possesses low latency and high concurrency. It creates interactive analytics that helps many organizations in creating analytics applications. It is a database that offers priority to factors like fast performance, real-time ingestion of data, and high uptime.

Salient Features:

• Lower latency for OLAP queries
• Adaptable schemas
• Column-oriented storage
• Fuelling GUIs of analytical applications
• Backend for highly concurrent APIs

Dremio:

Dremio is a popular cloud data analytics tool that provides analytical procedures executing on data lakes. It adapts different processes for data extraction. There is a centralized data catalog for different data sources.

Dremio assists in lessening the data warehousing costs associated with it. It has its in-memory software that helps execute analytical routines barring a data warehouse. As an easy-to-use and open lake house platform, Dremio offers an experience with an insightful UI for all.

Salient Features:

• Facilitates BI capabilities of all types
• Enterprise level security
• Cost efficacy with control
• Automatic onboarding with attractive UX
• Self-service data ingestion

Vertica:

Vertica is a known analytical database management tool that offers unified analytics with speed, inbuilt machine learning, and scalability. It is fast, advanced, and accessible on-premises n different platforms.

Vertica possesses a software-dependent analytical platform that helps companies of all sizes and segments in analyzing data in real-time to a large extent. It supports Big Data processing, columnar databases, and data warehousing.

Salient Features:

• Vast parallel processing
• Columnar orientation
• Automated database design
• Expanded cloud integration
• Progressive compression competencies

Snowflake Competitors: The Conclusion

As we browse through the list of possible Snowflake alternatives, it is understood that organizations must choose their preferred option based on certain parameters.

Though companies using Snowflake are quite contented, key underlying conditions such as the type of cloud-based service needed, budgeted cost, organizational objectives, skilled resource availability, etc. play a pivotal role in choosing the best Snowflake competitor.

To each its own!