This whitepaper compares the major cloud data warehouse and query engine options on AWS across more than 30 different categories including their overall architectures and core features, scalability, performance, and cost, as well as their suitability across these different analytics use cases. Read
The advent of cheap, infinite cloud storage and massive data collection from the web and IoT has dramatically transformed the nature of raw data subject to analytical query workloads. With endless streams of JSON log files and other nested serialization formats like Avro and Parquet, the ability to handle semi-structured data is a must. Read
The process of understanding cloud data warehouse pricing models is not straightforward, as they are dependent on different parameters like speed, scale and usage. In the following article we’ll review the most common pricing models, their pros and cons and which use-cases they are most relevant for. Read
When selecting a cloud data warehouse, technical and cost constraints make users compromise on certain features. The following checklist of criteria was written to help you determine which factors are most important for the success of your organization. Read
What are the technological concepts that make Snowflake so unique, and why has it proven to be so disruptive for the data warehousing space in particular? Read
For organizations to flourish today, they need to move fast. At the same time, moving fast and making data-driven decisions haven’t usually gone hand-in-hand together. Not yet anyway. Read
The current trends in data warehousing are oriented around cloud native architectures that take advantage of dynamic scaling and the separation of compute and storage. Firebolt is taking that a step further with a core focus on speed and interactivity. Listen
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