Based on our record, Apache ORC should be more popular than Upsolver. It has been mentiond 3 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
The information can be stored in a database or as files, serialized in a standard format and with a schema agreed with your Data Engineering team. Depending on your information and requirements, it can be as simple as CSV, XML or JSON, or Big Data formats such as Parquet, Avro, ORC, Arrow, or message serialization formats like Protocol Buffers, FlatBuffers, MessagePack, Thrift, or Cap'n Proto. - Source: dev.to / over 1 year ago
Data formatting is another place to make gains. When dealing with huge amounts of data, finding the data you need can take up a significant amount of your compute time. Apache Parquet and Apache ORC are columnar data formats optimized for analytics that pre-aggregate metadata about columns. If your EMR queries column intensive data like sum, max, or count, you can see significant speed improvements by reformatting... - Source: dev.to / over 2 years ago
The following stack captures layers of software components that make up Hudi, with each layer depending on and drawing strength from the layer below. Typically, data lake users write data out once using an open file format like Apache Parquet/ORC stored on top of extremely scalable cloud storage or distributed file systems. Hudi provides a self-managing data plane to ingest, transform and manage this data, in a... - Source: dev.to / almost 3 years ago
Most of the pains of using query engines over object storage are in the ongoing management of files (partitioning, compression, merging many small files into fewer larger files) Cloud data lakes are tremendously valuable when it comes to exploratory and ad-hoc data analysis. If you really require sub-second queries on structured data, you're better off with a data warehouse. I'm not totally clear on your use... Source: almost 3 years ago
Impala - Impala is a modern, open source, distributed SQL query engine for Apache Hadoop.
Kylo - Kylo is an end-to-end data lake management software that provides data from many sources in an automated fashion and optimizes it.
SQream - SQream empowers organizations to analyze the full scope of their Massive Data, from terabytes to petabytes, to achieve critical insights which were previously unattainable.
IRI Voracity - IRI Voracity is an automated data management platform that helps you extract, transform and load (ETL) your data lake to any data warehouse or cloud.
Apache Kudu - Apache Kudu is Hadoop's storage layer to enable fast analytics on fast data.
Mozart Data - The easiest way for teams to build a Modern Data Stack