The Hidden Costs of Cloud Data Lakes

This blog series from Cazena's engineering team investigates the hidden costs of cloud data lakes. Learn the top three hidden costs of cloud data lakes!

Read the Blog Series

End of The Line for Traditional Data Warehousing?

Big data, cloud and open-source technologies are revolutionizing data warehousing and traditional vendors are scrambling to adapt. Witness Actian ending support for Matrix (formerly ParAccel), Pivotal taking Greenplum database open source, and HPE spinning off Vertica and other assets. So it’s no surprise that data and analytics leaders want to explore their options when their old data warehouse platform nears the end of its life due to capacity limits, the end of vendor support, or data center consolidation.

In the face of this rapid evolution, many enterprises question the wisdom of locking in to yesteryear’s paradigm for another generation by making additional big investments in on-premises technologies like Oracle Exadata, Teradata, IBM Netezza, EMC DCA (Greenplum Database), Actian Matrix or Vertica. Migrating data warehouses to the cloud promises a more agile, cost-effective and scalable option.

However, data warehousing in the cloud is not just a matter of spinning up an Azure Data Warehouse or Redshift cluster. That’s the easy part! But just like a car is more than only an engine, an enterprise data warehouse is a complex system. Unless you’re building everything anew in the cloud from scratch, enterprises must figure out how to address security, data movement, integration with BI/analytics tools, data sources and related systems like ETL and MDM in the new context of cloud. Many are also thinking about the potential role of Hadoop and Spark, and whether those could cut costs and add capabilities. Suddenly the “simple” question of migration becomes a more complicated and strategic issue.

We built Cazena’s Big Data as a Service to seamlessly migrate data warehouses to Azure and AWS. Our service incorporates a variety of engines including MPP SQL, Hadoop, Spark and other technologies – and we’ve focused on ease of use, integration and how to stay connected with your existing data architecture.

Cazena’s platform has many built-in capabilities including on-premises to cloud data movement, security and compliance functions, intelligent provisioning and operations to quickly migrate production data warehouses to the cloud. Cazena also has the benchmark data and expertise to map your workloads to the best data and cloud technology combo to maximize price/performance. For example,

  • Moving classic BI/MPP SQL style workloads to our Data Mart as a Service, powered by Greenplum Database on Azure or AWS Redshift
  • Migrating ETL workloads from your data warehouse to our Data Lake as a Service leveraging Hadoop/Spark
  • Augmenting data warehouses with our Data Lake as a Service to support self-serve data science users utilizing R, Python, Scala, etc.

If you’d like to learn more about migrating data warehousing to the cloud, contact us for a demo or free Cazena test drive.

Related Resources