Data warehouses are used to employ data for deep analytics. One of the leading players in the data warehousing space is Snowflake.
US-based data warehousing company Snowflake Inc was founded in July 2012 by Benoit Dageville, Thierry Cruanes and Marcin Zukowski to address the challenges of companies having to buy expensive hardware appliances to run in their data centres for storing data. Its query engine is made in-house.
It offers fast, reliable, secure and cost-effective access to data by creating a single, governed and immediately available source. It has partnered with data integration and business intelligence solution providers, including Tableau, Qlik, Sigma, and Stitch, to provide seamless access of data by customers. Snowflake has worked on Amazon S3 since 2014, Microsoft Azure since 2018 and Google Cloud Platform since 2019.
In this list, we explore alternatives to Snowflake.
Google BigQuery
Google’s multi-cloud data warehouse BigQuery is highly scalable and designed for business agility. BigQuery claims to help businesses run analytics at scale with up to 34 percent lower three-year TCO than its alternatives. In addition, it seamlessly integrates with Google Suite products such as Google Analytics. However, it lacks integrations to be able to pull data from non-Google sources.
New customers of BigQuery get $300 free credits to spend on the first 90 days of using Google Cloud. Additionally, customers get 10 GB storage and up to 1 TB queries per month, for free of charge.
For more information, click here.
Amazon Redshift
Cloud-based data warehouse Amazon Redshift is a product of the Amazon Web Services cloud platform. Mostly designed for data scientists and data engineers, Redshift is fast and fully managed, making it simple and cost-effective to analyse data using SQL and existing BI tools.
However, Redshift users require third-party tools when it comes to ETL and data transformation. It is HIPAA and GDPR compliant. Redshift offers two months of a free trial, post which its pricing begins from $0.25 per hour.
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IBM Db2
IBM’s Db2 warehouse offers in-memory BLU processing technology and in-database analytics. It provides scalability and performance through MPP architecture and is compatible with Oracle and Netezza. Therefore, it is a suitable option for businesses that need to keep data on-premises or want the flexibility of the cloud without compromising on the privacy requirements. Additionally, IBM Db2 is ideal for businesses considering hybrid architecture to modernise its data warehouse.
For more information, click here.
Panoply
Co-founded by Yaniv Leven and Roi Avinoam, Panoply is an end-to-end cloud data warehouse and management service. Its no-code data integrations ensure zero maintenance. Its features include:
- Automatic data type detection.
- Built-in performance monitoring system.
- Hands-free scaling.
- Pre-built SQL queries.
As an ETL tool, Panoply comes with built-in ETL integrations to ready-to-use data sources. In addition, Panoply offers plug-and-play compatibility with analytic notebook and BI tools.
Panoply offers 14-days of free trial, after which it offers three different annual pricing options, starting with $399 per month.
For more information, click here.
Microsoft SQL Server
Microsoft SQL combines data analytics and warehousing, making it one of the most popular SQL database formats. It is used in Azure data warehouse and Microsoft transactional database. After the launch of Azure Synapse Analytics, Microsoft created an unified platform for ingesting, preparing, managing and serving data that can be channeled into BI and ML tools.
Microsoft SQL Server’s pricing is volume-dependent, however, the services can be availed for the first 180-days for free.
For more information, click here.
Azure Synapse Analytics
Azure Synapse Analytics brings together data integration, enterprise data warehousing and big data analytics. It is a cloud-based enterprise data warehouse. Azure Synapse Analytics leverages MPP to run complex queries across data. It allows ingestion, exploration, preparation, management and serving of data for immediate BI and ML needs.
For Azure Synapse Analytics, a customer only has to pay for the capabilities that they opt in to use.
For more information, click here.
Azure Data Lake Storage
Microsoft Azure Data Lake Storage allows developers, data scientists and analysts to store data of all size, shape and speed and perform all types of processing and analytics across platforms and languages. Furthermore, it integrates with existing operational stores and data warehouses, allowing one to extend their present data applications.
It is massively scalable and secures data lake for customers’ high-performance analytics workloads. Additionally, it offers a single storage platform for ingestion, processing and visualisation supporting common analytics frameworks.
For more information, click here.
Oracle Exadata Cloud Service
Oracle Exadata Cloud Service allows customers to run Oracle Database workloads in the cloud. Its infrastructure is isolated from other users, ensuring maximum security, performance and uptime.
Oracle Exadata Cloud Service is cost effective and reliable for data warehousing and business intelligence. In addition, it offers flexibility in licensing options. The first 30-days are free.
For more information, click here.
