Panoply
Supermetrics
QuickBI
Fivetran
Airbyte
Snowflakepowe.red
Google BigQuery
Amazon Redshift
Apache ORC
Apache Parquet
Amazon EMR
Apache Kudu
Impala
SQream
RJ Metrics
RocksDB
Panoply is a smart data warehouse that automates all three key aspects of the data analytics stack: data collection & transformation (ETL), database storage management, and query performance optimization. Panoply empowers anyone working with data analytics to quickly gain actionable insights on their own - without the need of IT and Engineering.
Panoply Apache ORCNo Apache ORC videos yet. You could help us improve this page by suggesting one.
Apache ORC might be a bit more popular than Panoply. We know about 3 links to it since March 2021 and only 3 links to Panoply. 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 service I used was Panoply. https://panoply.io/. Source: almost 2 years ago
Instead of building everything from scratch, you can try https://panoply.io/. Source: almost 2 years ago
Thanks will check this out. Currently we are testing with https://panoply.io/ but it's expensive. Source: over 2 years ago
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
Supermetrics - Supermetrics condenses all the major vectors of data relevant to a user's marketing campaigns and helps them make sense of it all.
Apache Parquet - Apache Parquet is a columnar storage format available to any project in the Hadoop ecosystem.
QuickBI - Export data from over 300 sources to a data warehouse and analyze it with a reporting tool of your choice. Quick and easy setup.
Amazon EMR - Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.
Fivetran - Fivetran offers companies a data connector for extracting data from many different cloud and database sources.
Apache Kudu - Apache Kudu is Hadoop's storage layer to enable fast analytics on fast data.
