The actual implementation of Presto versus Drill for your use case is really an exercise left to you. Apache Arrow is an open source technology Dremio helped create that also uses columnar data compression and many other optimizations that take advantage of in-memory computing and GPUs. Apache Arrow with Apache Spark. Disaggregated Coordinator (a.k.a. Does not need Hive metastore to query data on HDFS. Speed: Presto is faster due to its optimized query engine and is best suited for interactive analysis. Apache Arrow is integrated with Spark since version 2.3, exists good presentations about optimizing times avoiding serialization & deserialization process and integrating with other libraries like a presentation about accelerating Tensorflow Apache Arrow on Spark from Holden Karau. These two don't belong to the same category and don't compete with each other same as Arrow doesn't compete with Hadoop. Comparison with Hive. This post is focused on the performance of Presto, more specifically on the performance comparison between Amazon’s S3 object storage service and MinIO’s object storage software. It uses Apache Arrow for In-memory computations. In this post, I will share the difference in design goals. It was mainly targeted for Data Science workloads to use a … Presto allows for data queries that traverse data stores and locations - a big plus in the multi-everything world of big data analytics. Issue. Design Docs. CloudFlare: ClickHouse vs. Druid. Apache Arrow is an in-memory data structure specification for use by engineers building data systems. Other major Presto users include Netflix (using Presto for analyzing more than 10 PB data stored in AWS S3), AirBnb and Dropbox. It doesn’t require schema definition which could lead to … Throttling functionality may limit the concurrent queries. They needed 4 ClickHouse servers (than scaled to 9), and estimated that similar Druid deployment would need “hundreds of nodes”. Hive, in comparison is slower. One example that illustrates the problem described above is Marek VavruÅ¡a’s post about Cloudflare’s choice between ClickHouse and Druid. is it possible to query in memory arrow table using presto or is there some way to use a pandas data frame as a data source for presto query engine Ask Question Asked 2 years, 9 months ago Presto-on-Spark Runs Presto code as a library within Spark executor. Apache Arrow is a proposed in-memory data layer designed to back different analytical loads. Apache Pinot and Druid Connectors – Docs. It shares same features with Presto which makes it a good competitor. Apache Spark is a storage agnostic cluster computing framework. 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