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Apache Parquet is a free and open-source column-oriented data storage format in the Apache Hadoop ecosystem. It is similar to RCFile and ORC, the other columnar-storage file formats in Hadoop, and is compatible with most of the data processing frameworks around Hadoop.
^ The primary format is binary, but text and JSON formats are available. [8] [9] ^ Means that generic tools/libraries know how to encode, decode, and dereference a reference to another piece of data in the same document. A tool may require the IDL file, but no more. Excludes custom, non-standardized referencing techniques.
FES (file format) – 3D Topicscape file, produced when a fileless occurrence in 3D Topicscape is exported to Windows. Used to permit round-trip (export Topicscape, change files and folders as desired, re-import them to 3D Topicscape) MGMF – MindGenius Mind Mapping Software file format; MM – FreeMind mind map file (XML)
Hierarchical Data Format (HDF) is a set of file formats (HDF4, HDF5) designed to store and organize large amounts of data.Originally developed at the U.S. National Center for Supercomputing Applications, it is supported by The HDF Group, a non-profit corporation whose mission is to ensure continued development of HDF5 technologies and the continued accessibility of data stored in HDF.
Data orientation is the representation of tabular data in a linear memory model such as in-disk or in-memory.The two most common representations are column-oriented (columnar format) and row-oriented (row format). [1] [2] The choice of data orientation is a trade-off and an architectural decision in databases, query engines, and numerical ...
Apache Parquet and Apache ORC are popular examples of on-disk columnar data formats. Arrow is designed as a complement to these formats for processing data in-memory. [11] The hardware resource engineering trade-offs for in-memory processing vary from those associated with on-disk storage. [12]
Trino is an open-source distributed SQL query engine designed to query large data sets distributed over one or more heterogeneous data sources. [1] Trino can query data lakes that contain a variety of file formats such as simple row-oriented CSV and JSON data files to more performant open column-oriented data file formats like ORC or Parquet [2] [3] residing on different storage systems like ...
While using SQL for queries, DuckDB targets serverless applications and provides extremely fast responses using Apache Parquet files for storage. These attributes make it a popular choice for large dataset analysis in interactive mode, but certain commenters [ who? ] have indicated that they believe the serverless nature of DuckDB makes it, as ...