Comparing Impala To Redshift

Mostafa Mokhtar, et al, have a comparison of Apache Impala to Amazon Redshift:

For this analysis, we used TPC-DS on a 3TB dataset and selected 70 out of 99 the queries that run without any modifications or uses variants on both Redshift and Impala. We wanted to use a larger dataset (similar to what we’ve used in previous benchmarks), but due to Redshift’s data load times, we had to reduce the data size. (Note: This benchmark is derived from the TPC-DS benchmark and, as such, is not directly comparable to published TPC-DS results.)

This is coming from one of the two vendors, so take it with however many grains of salt you’d like.

Related Posts

Testing Kafka Streams Applications

Yeva Byzek continues her series on testing Kafka-based streaming applications: When you create a stream processing application with Kafka’s Streams API, you create a Topologyeither using the StreamsBuilder DSL or the low-level Processor API. Normally, the topology runs with the KafkaStreams class, which connects to a Kafka cluster and begins processing when you call start(). For testing though, connecting to a running […]

Read More

Auto ML With SQL Server 2019 Big Data Clusters

Marco Inchiosa has a model scenario for using Big Data Clusters to scale out a machine learning problem: H2O provides popular open source software for data science and machine learning on big data, including Apache SparkTM integration. It provides two open source python AutoML classes: h2o.automl.H2OAutoML and pysparkling.ml.H2OAutoML. Both APIs use the same underlying algorithm implementations, […]

Read More

Categories

September 2016
MTWTFSS
« Aug Oct »
 1234
567891011
12131415161718
19202122232425
2627282930