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  2. Google data centers - Wikipedia

    en.wikipedia.org/wiki/Google_data_centers

    Google data centers are the large data center facilities Google uses to provide their services, which combine large drives, computer nodes organized in aisles of racks, internal and external networking, environmental controls (mainly cooling and humidification control), and operations software (especially as concerns load balancing and fault tolerance).

  3. BigQuery - Wikipedia

    en.wikipedia.org/wiki/BigQuery

    BigQuery is a managed, serverless data warehouse product by Google, offering scalable analysis over large quantities of data. It is a Platform as a Service that supports querying using a dialect of SQL. It also has built-in machine learning capabilities. BigQuery was announced in May 2010 and made generally available in November 2011.

  4. Looker Studio - Wikipedia

    en.wikipedia.org/wiki/Looker_Studio

    Initially, Google Data Studio and Looker operated as separate products within Google. Google Data Studio's offering was a simple, low-cost, and easy way to connect data sources and create dashboards, [ 11 ] while Looker offered a more enterprise-focused solution with robust support for transformations and permissions.

  5. Protocol Buffers - Wikipedia

    en.wikipedia.org/wiki/Protocol_Buffers

    Data structure schemas (called messages) and services are described in a proto definition file (.proto) and compiled with protoc. This compilation generates code that can be invoked by a sender or recipient of these data structures. For example, example.pb.cc and example.pb.h are generated from example.proto.

  6. List of statistical software - Wikipedia

    en.wikipedia.org/wiki/List_of_statistical_software

    Pandas – High-performance computing (HPC) data structures and data analysis tools for Python in Python and Cython (statsmodels, scikit-learn) Perl Data Language – Scientific computing with Perl; Ploticus – software for generating a variety of graphs from raw data; PSPP – A free software alternative to IBM SPSS Statistics

  7. RocksDB - Wikipedia

    en.wikipedia.org/wiki/RocksDB

    It is a fork of Google's LevelDB optimized to exploit multi-core processors (CPUs), and make efficient use of fast storage, such as solid-state drives (SSD), for input/output (I/O) bound workloads. It is based on a log-structured merge-tree (LSM tree) data structure.

  8. GLOP - Wikipedia

    en.wikipedia.org/wiki/GLOP

    GLOP (the Google Linear Optimization Package) is Google's open-source linear programming solver, created by Google's Operations Research Team. It is written in C++ and was released to the public as part of Google's OR-Tools software suite in 2014. [1] GLOP uses a revised primal-dual simplex algorithm optimized for sparse matrices.

  9. EMBOSS - Wikipedia

    en.wikipedia.org/wiki/EMBOSS

    EMBOSS is a free c software analysis package developed for the needs of the molecular biology and bioinformatics user community. [1] The software automatically copes with data in a variety of formats and even allows transparent retrieval of sequence data from the web.

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