Search Results for "performance"
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Showing 19 open source projects for "performance"
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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Cut Data Warehouse Costs by 54%BigQuery delivers 54% lower TCO with exabyte scale and flexible pricing. Free migration tools handle the SQL translation automatically.
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pandas
Fast, flexible and powerful Python data analysis toolkit
pandas is a Python data analysis library that provides high-performance, user friendly data structures and data analysis tools for the Python programming language. It enables you to carry out entire data analysis workflows in Python without having to switch to a more domain specific language. With pandas, performance, productivity and collaboration in doing data analysis in Python can significantly increase. -
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LinDB
LinDB is a scalable, high performance, high availability database
LinDB is a scalable, high-performance, high-availability distributed time series database. A single server could easily support more than one million write TPS; With fundamental techniques like efficient compression storage and parallel computing, LinDB delivers highly optimized query performance. The multi-channel replication protocol supports any amount of nodes, and ensures the system's availability. -
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StarRocks
StarRocks is a next-gen sub-second MPP database for full analytics
...All of your BI tools work with StarRocks through standard SQL. StarRocks provides superior performance. It is also a unified OLAP covering most data analytics scenarios. -
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F1 Race Replay
An interactive Formula 1 race visualisation and data analysis tool
...It ingests official timing and positional data, then renders vehicle movements through track maps and 3D visualizations so fans, analysts, and engineers can review strategy, overtakes, tire degradation effects, and pit stop impacts in detail. Users can scrub through time, jump between cars, and overlay performance graphs such as speed, sector times, and gap differentials to evaluate performance trends across laps. This deep dive capability turns passive viewing into active exploration, empowering enthusiasts and professionals to discover insights usually hidden in raw data. The viewer also supports annotations and bookmark capabilities so users can mark moments of interest for future review or comparison. -
$300 Free Credits to Build on Google CloudStart your next project with $300 in free Google Cloud credit. Spin up VMs, run containers, query petabytes in BigQuery, or build agents with Gemini Enterprise Agent Platform. Once your credits are used, keep building with 20+ always-free tier products including Compute Engine, Cloud Storage, GKE, and Cloud Run functions. No commitment required—just sign up and start building.
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IoTDB
Apache IoTDB
Apache IoTDB (Database for Internet of Things) is an IoT native database with high performance for data management and analysis, deployable on the edge and the cloud. Due to its light-weight architecture, high performance and rich feature set together with its deep integration with Apache Hadoop, Spark and Flink, Apache IoTDB can meet the requirements of massive data storage, high-speed data ingestion and complex data analysis in the IoT industrial fields. -
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DuckDB
DuckDB is an in-process SQL OLAP Database Management System
DuckDB is a high-performance analytical database system. It is designed to be fast, reliable and easy to use. DuckDB provides a rich SQL dialect, with support far beyond basic SQL. DuckDB supports arbitrary and nested correlated subqueries, window functions, collations, complex types (arrays, structs), and more. For more information on the goals of DuckDB, please refer to the Why DuckDB page on our website. -
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Countly iOS SDK
Countly Product Analytics iOS SDK with macOS, watchOS and tvOS support
Countly SDK for iOS is an analytics SDK for integrating real-time event tracking, user profiles, crash reporting, and push notifications into iOS apps. It provides detailed insights into user behavior and app performance. -
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SageMaker Spark Container
Docker image used to run data processing workloads
Apache Spark™ is a unified analytics engine for large-scale data processing. It provides high-level APIs in Scala, Java, Python, and R, and an optimized engine that supports general computation graphs for data analysis. It also supports a rich set of higher-level tools including Spark SQL for SQL and DataFrames, MLlib for machine learning, GraphX for graph processing, and Structured Streaming for stream processing. The SageMaker Spark Container is a Docker image used to run batch data... -
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dlib
Toolkit for making machine learning and data analysis applications
Dlib is a modern C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems. It is used in both industry and academia in a wide range of domains including robotics, embedded devices, mobile phones, and large high performance computing environments. Dlib's open source licensing allows you to use it in any application, free of charge. Good unit test coverage, the ratio of unit test lines of code to library lines of code is about 1 to 4. The library is tested regularly on MS Windows, Linux, and Mac OS X systems. No other packages are required to use the library, only APIs that are provided by an out of the box OS are needed. ... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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POCO
Cross-platform C++ libraries for building network applications
The POCO C++ Libraries are powerful cross-platform C++ libraries for building network- and internet-based applications that run on desktop, server, mobile, IoT, and embedded systems. Whether building automation systems, industrial automation, IoT platforms, air traffic management systems, enterprise IT application and infrastructure management, security and network analytics, automotive infotainment and telematics, financial or healthcare, C++ developers have been trusting the POCO C++... -
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.NET for Apache Spark
A free, open-source, and cross-platform big data analytics framework
.NET for Apache Spark provides high-performance APIs for using Apache Spark from C# and F#. With these .NET APIs, you can access the most popular Dataframe and SparkSQL aspects of Apache Spark, for working with structured data, and Spark Structured Streaming, for working with streaming data. .NET for Apache Spark is compliant with .NET Standard - a formal specification of .NET APIs that are common across .NET implementations. -
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TensorBase
TensorBase is a new big data warehousing with modern efforts
...After thoughts, we decided to temporarily leave the general data warehousing field. For people who want to learn how a database system can be built up, or how to apply modern Rust to the high-performance field, or embed a lightweight data analysis system into your own big one. You can still try, ask or contribute to TensorBase. The committers are still around the community. We will help you in all kinds of interesting things pursued in the project by us and maybe you. We still maintain the project to look forward to meeting more database geniuses in this world, although no new feature will be added in the near future. -
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Newsvendor Model Simulation Spreadsheet
Excel Spreadsheet Model for Single Period Inventory Problems
...The newsvendor problem. White Paper, 57-23. Lawrence, J. A., & Pasternack, B. A. (2002). Applied management science. Willey, Chichester. Microsoft. Office Dev Center (2017). Excel performance: Improving calculation per -
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Feather
Binary data frame storage for Python, R, and more
Feather is a fast, interoperable binary data frame storage format designed for efficient data exchange between analysis tools. It provides columnar serialization for data frames, making read and write operations faster than many text-based formats. The project was built to make sharing data across languages such as Python and R easier. Feather is powered by the Apache Arrow columnar memory specification, which helps it represent numeric, string, categorical, date, timestamp, boolean, and... -
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postgresqltuner.pl
Simple script to analyse your PostgreSQL database configuration
postgresqltuner is a Perl script designed to analyze PostgreSQL database configurations and provide tuning advice. It assists database administrators in optimizing performance by offering recommendations based on the current setup. -
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Central Proteomics Facilities Pipeline
A data analysis pipeline for shotgun mass-spectrometry proteomics.
...However: * Limited fixes have been made on the main master branch by Phil Charles at the University of Oxford. * As of 2019, limited maintenance is being carried out by myself (now in the BioHPC high performance computing group at UTSW), to allow CPFP to install and run on RHEL 7 / CentOS 7, with updated TPP 5.1.0 and search tools. This updated code can be found in the utsw-biohpc branch of the git repository, and may become a 2.2.0 release if time and testing allows. -- David Trudgian - 2019/01/03 -
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jFox Journal
Trading journal for Currency,Stock,Commodity traders
jFox Trading Journal is software developed mainly for currency traders,it provides advanced data analysis to improve traders ability to reach higher profits and eliminate losses.jFox keeps your data in one place.To access or modify any of your data jFox provide simple user friendly GUI.By generating graphs and statistics automaticly,user only needs to provide his data to have full overview over his trades and trading performance. -
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Parallel Colt is a multithreaded version of Colt - a library for high performance scientific computing in Java. It contains efficient algorithms for data analysis, linear algebra, multi-dimensional arrays, Fourier transforms, statistics and histogramming
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ROOTSNNS is a set of C++ classes which allows one to use the Stuttgart Neural Network Simulator kernel (ansi-C) within the ROOT, a data analysis package. Multiple ANNs can be built, trained, and tested, while results and ANN performance can be saved.
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