Here’s the difference between Redshift and Apache Spark. The comparison is based on pricing, deployment, business model, and other important factors.
Amazon Redshift is a fully managed petabyte scale data warehouse service. Redshift is designed for analytic workloads and connects to standard SQL based clients and business intelligence tools. Redshift delivers fast query and I/O performance for virtually any size dataset by using columnar storage technology and parallelizing and distributing queries across multiple nodes. Most common administrative tasks associated with provisioning, configuring, monitoring, backing up, and securing a data warehouse are automated.
Apache Spark is an open-source unified analytics engine for large-scale data processing. Spark provides an interface for programming entire clusters with implicit data parallelism and fault tolerance.
Overview | ||
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Categories | Data Warehouses | Data Modelling and Transformation |
Stage | Late Stage | Late Stage |
Target Segment | Enterprise | Mid Size, Enterprise |
Deployment | SaaS | On Prem |
Business Model | Commercial | Open Source |
Pricing | Freemium | Freemium |
Location | Seattle,WA, US | US |
Companies using it | ||
Contact info |