SQream
GridGain In-Memory Data Fabric
Panoply
CAKE
RJ Metrics
Impala
Fujitsu Symfoware Analytics Server
Amazon EMR
Apache ORC
Apache Parquet
Amazon EMR
Apache Kudu
Impala
RJ Metrics
RocksDB
Microsoft SQL
SQream is a data analytics acceleration platform built especially for massive data - from terabytes to petabytes. SQream takes queries down from days to hours and hours to minutes. The SQream platform provides the ability to analyze more data, faster, with multiple dimensions and cuts data preparation significantly by enabling ad-hoc querying on raw data. Leading global organizations in telecommunications, healthcare, ad-tech, retail and more rely on SQream to achieve critical business insights and potentially valuable BI across their massive data stores.
SQream Apache ORCNo Apache ORC videos yet. You could help us improve this page by suggesting one.
Based on our record, Apache ORC should be more popular than SQream. 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.
Later on, when your needs will increase, you can work with https://sqream.com/ (Panoply was acquired by SQream DB). Source: about 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
GridGain In-Memory Data Fabric - TheGridGain In-Memory Computing Platform is a comprehensive solution provides speed and scale for data intensive applications across any data store
Apache Parquet - Apache Parquet is a columnar storage format available to any project in the Hadoop ecosystem.
Panoply - Panoply is a smart cloud data warehouse
Amazon EMR - Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.
CAKE - CAKE provides a SaaS-based solution for advertisers, publishers and networks to track, attribute and optimize their spend in real-time.
Apache Kudu - Apache Kudu is Hadoop's storage layer to enable fast analytics on fast data.
