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Dremel (software)
Dremel is a distributed system developed at Google for interactively querying large datasets. Dremel is the query engine used in Google's BigQuery service. Dremel is the inspiration for Apache Drill, Apache Impala Apache Impala is an open source massively parallel processing (MPP) SQL query engine for data stored in a computer cluster running Apache Hadoop. Impala has been described as the open-source equivalent of Google F1, which inspired its developmen ..., and Dremio, an Apache licensed platform that includes a distributed SQL execution engine. In 2020, Dremel won the Test of Time award at the VLDB 2020 conference recognizing the innovations it pioneered. References * Google software {{google-stub ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
BigQuery
BigQuery is a fully managed, serverless data warehouse that enables scalable analysis over petabytes of data. It is a ''Platform as a Service'' (PaaS) that supports querying using ANSI SQL. It also has built-in machine learning capabilities. BigQuery was announced in May 2010 and made generally available in November 2011. Design BigQuery provides external access to Google's Dremel technology, a scalable, interactive ''ad hoc'' query system for analysis of nested data. BigQuery requires all requests to be authenticated, supporting a number of Google-proprietary mechanisms as well as OAuth. Features * Managing data - Create and delete objects such as tables, views, and user defined functions. Import data from Google Storage in formats such as CSV, Parquet, Avro or JSON. * Query - Queries are expressed in a standard SQL dialect and the results are returned in JSON with a maximum reply length of approximately 128 MB, or an unlimited size when large query results are enabled. ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Apache Drill
Apache Drill is an open-source software framework that supports data-intensive distributed applications for interactive analysis of large-scale datasets. Built chiefly by contributions from developers from MapR, Drill is inspired by Google's Dremel system, also productized as BigQuery. Drill is an Apache top-level project. Tom Shiran is the founder of the Apache Drill Project. It was designated an Apache Software Foundation top-level project in December 2016. Drill supports a variety of NoSQL databases and file systems, including Alluxio, HBase, MongoDB, MapR-DB, HDFS, MapR-FS, Amazon S3, Azure Blob Storage, Google Cloud Storage, Swift, NAS and local files. A single query can join data from multiple datastores. For example, you can join a user profile collection in MongoDB with a directory of event logs in Hadoop. Drill's datastore-aware optimizer automatically restructures a query plan to leverage the datastore's internal processing capabilities. In addition, Drill suppor ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Apache Impala
Apache Impala is an open source massively parallel processing (MPP) SQL query engine for data stored in a computer cluster running Apache Hadoop. Impala has been described as the open-source equivalent of Google F1, which inspired its development in 2012. Description Apache Impala is a query engine that runs on Apache Hadoop. The project was announced in October 2012 with a public beta test distribution and became generally available in May 2013. Impala brings scalable parallel database technology to Hadoop, enabling users to issue low-latency SQL queries to data stored in HDFS and Apache HBase without requiring data movement or transformation. Impala is integrated with Hadoop to use the same file and data formats, metadata, security and resource management frameworks used by MapReduce, Apache Hive, Apache Pig and other Hadoop software. Impala is promoted for analysts and data scientists to perform analytics on data stored in Hadoop via SQL or business intelligence tools. The ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
VLDB Conference
International Conference on Very Large Data Bases or VLDB conference is an annual conference held by the non-profit ''Very Large Data Base Endowment Inc.'' While named after very large databases, the conference covers the research and development results in the broader field of database management. The mission of VLDB Endowment is to "promote and exchange scholarly work in databases and related fields throughout the world." The VLDB conference began in 1975 and is now closely associated with SIGMOD and SIGKDD. Venues See also * XLDB XLDB (eXtremely Large DataBases) is a yearly conference about databases, data management and analytics. The definition of ''extremely large'' refers to data sets that are too big in terms of volume (too much), and/or velocity (too fast), and/or va ... References External links VLDB Endowment Inc. {{Authority control Computer science conferences ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |