Search Results for "performance"
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Showing 27 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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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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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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JuiceFS
JuiceFS is a distributed POSIX file system built on top of Redis
...Purposely built to serve big data scenarios such as self-driving model training, recommendation engine, and Next-generation Gene Sequencing, JuiceFS specializes in high performance and easier management of tens of billion of files management. We bring JuiceFS to developers with the hope that it will be easy to use, reliable, high-performance, and solve all your file storage problems in a cloud environment. -
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Fluid
Fluid, elastic data abstraction and acceleration for BigData/AI apps
...Enable dataset warmup and acceleration for data-intensive applications by using a distributed cache in Kubernetes with observability, portability, and scalability. Taking characteristics of application and data into consideration for cloud application/dataset scheduling to improve the performance. -
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FinMind
Open Data, more than 50 financial data
...For individual stocks, provide visual analysis of technical, fundamental, and chip levels. According to different strategies, back-test analysis is performed to provide performance, profit and loss, and stock selection targets of different strategy investment portfolios. -
Secure File Transfer for Windows with Cerberus by RedwoodCerberus supports unlimited users and connections on a single IP, with built-in encryption, 2FA, and a browser-based web client — all deployable in under 15 minutes with a 25-day free trial.
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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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GridDB
GridDB is a next-generation open source database
A cyber-physical systems is a system that collects a variety of data in physical space (the real world), analyzes and converts it into knowledge in cyberspace, and feeds the knowledge back to the real world to revitalize industry and solve social problems. GridDB is an open database that enables real-time processing of vast amounts of time-series data in physical space, which is necessary to realize a cyber-physical system. Multi-model architecture capable of supporting various data stores... -
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HugeGraph
A graph database that supports more than 100+ billion data
HugeGraph is a convenient, efficient, and adaptable graph database compatible with the Apache TinkerPop3 framework and the Gremlin query language. HugeGraph supports fast import performance in the case of more than 10 billion Vertices and Edges Graph, millisecond-level OLTP query capability, and can be integrated into big data platforms like Hadoop or Spark for OLAP analysis. The main scenarios of HugeGraph include correlation search, fraud detection, and knowledge graph. Not only supports Gremlin graph query language and RESTful API but also provides commonly used graph algorithm APIs. ... -
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Vespa
The open big data serving engine
Make AI-driven decisions using your data, in real-time. At any scale, with unbeatable performance. Vespa is a full-featured text search engine and supports both regular text search and fast approximate vector search (ANN). This makes it easy to create high-performing search applications at any scale, whether you want to use traditional techniques or a modern vector-based approach. You can even combine both approaches efficiently in the same query, something no other engine can do. ... -
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Apache RocketMQ
Distributed messaging and streaming platform with low latency
Apache RocketMQ is a distributed messaging and streaming platform with low latency, high performance and reliability, trillion-level capacity and flexible scalability. Messaging patterns including publish/subscribe, request/reply and streaming. Financial grade transactional message. Built-in fault tolerance and high availability configuration options base on DLedger. A variety of cross language clients, such as Java, C/C++, Python, Go. -
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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Nebula Graph
A distributed, fast open-source graph database
The graph database built for super large-scale graphs with milliseconds of latency. Optimized SUBGRAPH and FIND PATH for better performance. Optimized query paths to reduce redundant paths and time complexity. Optimized the method to get properties for better performance of MATCH statements. Nebula Graph adopts the Apache 2.0 license, one of the most permissive free software licenses in the world. Free as in freedom, because, under the Apache 2.0 license, you can use, copy, modify and redistribute Nebula Graph, even for commercial purposes, all without asking for permission. ... -
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gravitino
Unified metadata lake for data & AI assets.
Apache Gravitino is a high-performance, geo-distributed, and federated metadata lake. It manages metadata directly in different sources, types, and regions, providing users with unified metadata access for data and AI assets. -
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HPCC Systems
End-to-end big data in a massively scalable supercomputing platform.
Important: As of April 20, 2026, this project can now be found at https://github.com/hpcc-systems/HPCC-Platform/releases. HPCC Systems® (www.hpccsystems.com) from LexisNexis® Risk Solutions is a proven, open source solution for Big Data insights that can be implemented by businesses of all sizes. With HPCC Systems, developers can design applications with Big Data at their core, enabling businesses to better analyze and understand data at scale, improving business time to results and... -
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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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SZT-bigdata
SZT‑bigdata is an open source project
SZT‑bigdata is an open-source project analyzing real Shenzhen metro (subway) card usage data using big‑data frameworks like Spark, Hadoop, Hive, Kafka, Flink, ClickHouse, HBase, and Elasticsearch. Aimed at exploring transit passenger flow patterns and system optimization using a variety of Scala-based technologies. -
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MyCAT
Active, high-performance open source database middleware
MyCAT is an Open-Source software, “a large database cluster” oriented to enterprises. MyCAT is an enforced database which is a replacement for MySQL and supports transaction and ACID. Regarded as MySQL cluster of enterprise database, MyCAT can take the place of expensive Oracle cluster. MyCAT is also a new type of database, which seems like a SQL Server integrated with the memory cache technology, NoSQL technology and HDFS big data. And as a new modern enterprise database product, MyCAT is... -
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Open Source Data Quality and Profiling
World's first open source data quality & data preparation project
...Data Quality includes profiling, filtering, governance, similarity check, data enrichment alteration, real time alerting, basket analysis, bubble chart Warehouse validation, single customer view etc. defined by Strategy. This tool is developing high performance integrated data management platform which will seamlessly do Data Integration, Data Profiling, Data Quality, Data Preparation, Dummy Data Creation, Meta Data Discovery, Anomaly Discovery, Data Cleansing, Reporting and Analytic. It also had Hadoop ( Big data ) support to move files to/from Hadoop Grid, Create, Load and Profile Hive Tables. ... -
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inMap
Rich layers, better user experience, big data geographic visualization
inMap is a big data visualization library based on Baidu Map. It focuses on the display of scatter, heat map, grid, and aggregation in the direction of big data. It is committed to making big data visualization easy to use. -
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MarDRe
MapReduce-based tool to remove duplicate DNA reads
...MarDRe is the Big Data counterpart of ParDRe (link above), which employs HPC technologies (i.e., hybrid MPI/multithreading) to reduce runtime on multicore systems. Instead, MarDRe takes advantage of the MapReduce programming model to significantly improve ParDRe performance on distributed systems, especially on cloud-based infrastructures. Written in pure Java to maximize cross-platform compatibility, MarDRe is built upon the open-source Apache Hadoop project, the most popular distributed computing framework for Big Data processing. -
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X10
Performance and Productivity at Scale
X10 is a class-based, strongly-typed, garbage-collected, object-oriented language. To support concurrency and distribution, X10 uses the Asynchronous Partitioned Global Address Space programming model (APGAS). This model introduces two key concepts -- places and asynchronous tasks -- and a few mechanisms for coordination. With these, APGAS can express both regular and irregular parallelism, message-passing-style and active-message-style computations, fork-join and bulk-synchronous... -
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fooltrader
Quant framework for stock
...Its applicable objects include quantitative traders, teachers, and students majoring in finance, people interested in economic data, programmers, and people who like freedom and the spirit of exploration. You could write the Strategy using an event-driven or time walkway and view and analyze the performance in a uniform way. -
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Vaex
Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python
...Vaex uses memory mapping, zero memory copy policy and lazy computations for best performance (no memory wasted). Cut development cut development time by 80%. Your prototype is your solution. Create automatic pipelines for any model. -
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Red-RF
Reduced Random Forest for big data
Red(uced)-RF, a new type of Random Forests that adopts dynamic data reduction and weighted upvoting techniques. Red-RF is favorably applicable to big data: it demonstrates an accurate and efficient performance while achieving a considerable data reduction w.r.t. dataset size. Manuscripts available on IEEE Xplore: H. Mohsen, H. Kurban, K. Zimmer, M. Jenne and M. Dalkilic. Red-RF: Reduced Random Forests using priority voting & dynamic data reduction. In IEEE BigData Congress'2015. H. Mohsen, H. Kurban, M. Jenne and M. Dalkilic (2014). ... -
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...It is an efficient tool for optimization and comparison of the state-of-the-art ranking classifiers by generating over 20 different high quality two- and three-dimensional performance curves.
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...It is an efficient tool for optimization and comparison of the state-of-the-art ranking classifiers by generating over 20 different high quality two- and three-dimensional performance curves.
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Streams for IBM i
Batch performance boosting and Big Data framework for IBM i
Streamd for IBM i is a suite of tools for IBM i (previously known as AS/400 and iSeries) that can significantly improve performance characteristics of batch processes. Due to extensive use of parallel programming techniques Streams for IBM i delivers significant performance improvements for single streamed batch jobs. Streams for IBM i can split an existing batch process into a number of concurrent streams, completely eliminate backup-related delays, introduce new robust recovery policies and even modify the program logic of existing applications - all without any code modifications. ...
