Top Cloud Data Warehouse Solutions for Your Business
A cloud data warehouse is a repository that collects data from multiple sources and stores it in a public cloud. It is built of high-performance analytics and offers functionality in terms of scalability, flexibility, security, and reliability. Cloud-driven data warehouses help companies achieve actionable customer insights, allowing them to drive sales and ensure exceptional customer experiences in a cost-effective way. Choosing the right vendor and the optimal data warehouse technology can be a complex process. To make your search seamless and easier, we’ve listed below the best cloud data warehouse solutions.
Microsoft
Platform: Azure Synapse
Description: Microsoft Azure Synapse is an analytics service that includes big data analytics, data integration, and enterprise data warehousing. This solution is ideal for integrating data from multiple data sources across a company’s divisions to perform analytical queries in seconds. It enables a unified experience to prepare and serve data for machine learning and business intelligence. It also offers advanced privacy and security features like dynamic masking and row-level security.
Google Cloud
Platform: Google BigQuery
Description: Google offers a fully-managed enterprise data warehouse for analytics via its BigQuery product in a cost-effective way. The serverless solution enables organizations to conduct data analysis by creating a logical data warehouse over data from spreadsheets. BigQuery is built atop the Google Cloud platform to capture data in real-time with the use of a streaming ingestion feature. This tool also allows users the ability to share insights in the form of spreadsheets, reports, and queries.
Snowflake
Platform: Snowflake Cloud Data Platform
Description: Snowflake, provided as Software-as-a-Service, offers a cloud data warehouse built atop Amazon Web Services. The solution enables organizations to concurrently allocate compute resources, both structured and unstructured, to the same database for loading and querying data with no impact on the data warehouse performance. Snowflake features support standard SQL and users can do analytical functions, updates, transactions, and deletes as a result. The columnar database engine requires no infrastructure and zero management uses advanced optimizations to process reports, crunch data, and run analytics.
Amazon Web Services
Platform: Amazon Redshift
Description: Amazon Redshift, a fully-managed cloud data warehouse, enables SQL-querying of exabytes of unstructured, structured, semi-structured data across operational data stores and data warehouses. With the use of familiar SQL-driven tools and business intelligence applications, Redshift offers fast query performance and hosts multiple ways to do cluster management. Amazon Redshift provides a data lake with the possibility to aggregate data with big data analytics and ML services.
SAP
Platform: SAP Data Warehouse Cloud
Description: Built on the SAP HANA Cloud database, it is a data warehouse service that connects data across multi-cloud and on-prem repositories in near real-time while preserving the business value. Also, the solution enables users to visualize and share data within a secure environment. The product includes semantic views of SAP application data and transformation logic to utilize the vendor’s expertise from its ecosystem of business partners.
IBM
Platform: IBM Db2 Warehouse
Description: The client-managed, preconfigured IBM Db2 warehouse, is run on private clouds, virtual private clouds, and other container-supported infrastructures. The product features built-in machine learning, built-in analytics, SMP & MPP processing, and automated scaling. With its flexible deployment infrastructure, Db2 users can write applications once and migrate them to the right location with less or no changes required. The other characteristics include but are not limited to PDA and Oracle, fast query processing, embedded Apache Spark engine, and compatibility with Db2.
Oracle
Platform: Oracle Autonomous Data Warehouse
Description: This cloud data warehouse service helps businesses secure data and build data-driven applications. Oracle Autonomous Data Warehouse includes self-service data loading tools and other tools for automatic insights, data transformations, built-in coverage for database capabilities, and business models that enable queries across various data types and analysis of machine learning. Oracle automates the process of provisioning, tuning, scaling, configuring, and backing up the data warehouse along.
Yellowbrick Data
Platform: Yellowbrick Data Warehouse
Description: Yellowbrick Data provides a data warehouse for distributed clouds to let customers deploy in public clouds, private data centers, and the network edge. By following the latest software and hardware advancements, it executes smart thinking about database foundation. Yellowbrick touts a modern analytic database designed to drive real-time, interactive, and mixed workloads. As a result, it is quickly provisioned and easy to use despite its deployment way.
Panoply
Platform: Panoply
Description: Panoply is a smart data warehouse that automates data management tasks linked with running big data on the cloud. It features an ETL-less integration pipeline to connect both structured and semi-structured data sources. Panoply offers columnar storage and enables automatic data backup to a redundant S3 storage architecture.
Teradata
Platform: Teradata Vantage
Description: Teradata offers a wide variety of data management solutions that include, but are not limited to data warehouse appliances, database management, and cloud data warehousing. The product portfolio of an organization is easily accessible on its own managed cloud and on Microsoft Azure or Amazon Web Services. Teradata offers the ability to organizations to run diverse queries efficiently in-database analytics and complex workload management.
Conclusion
It is evident that not all cloud-based data warehouses are the same, choosing the right one for your organization can be a daunting task. With data considered as one of the most crucial resources for organizations, warehousing solutions are more important than ever. By evaluating both your present and futuristic data warehouse needs, it is easy to determine which solution would be an ideal fit.
