Search Results for "high"
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Showing 22 open source projects for "high"
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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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$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
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pandas
Fast, flexible and powerful Python data analysis toolkit
...pandas is continuously being developed to be a fundamental high-level building block for doing practical, real world data analysis in Python, as well as powerful and flexible open source data analysis/ manipulation tool for any language. -
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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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ElasticJob
Distributed scheduled job framework
...ElasticJob-Cloud uses Mesos to manage and isolate resources. It uses a unified job API for each project. Developers only need code one time and can deploy at will. Support job sharding and high availability in distributed system. Scale out for throughput and efficiency improvement. Job processing capacity is flexible and scalable with the allocation of resources. Execute job on suitable time and assigned resources. Aggregation same job to same job executor. Append resources to newly assigned jobs dynamically. Using ElasticJob can make developers no longer worry about the non-functional requirements such as jobs scale out, so that they can focus more on business coding. -
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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. -
Error to trace to log to deploy. One click. No SSH.AppSignal links every error to the trace, the trace to the log, the log to the deploy that shipped it.
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Vespa
The open big data serving engine
...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. Recommendation, personalization and targeting involves evaluating recommender models over content items to select the best ones. ... -
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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
...Multi-model architecture capable of supporting various data stores with time-series data-oriented and pluggable data stores for efficient real-time processing and management of huge amounts of time-series data at high frequency. Various architectural innovations, such as in-memory orientation with "memory as the main unit and disk as the secondary unit" and event-driven design with minimal overhead, have been incorporated to achieve processing capabilities that can handle petabyte-scale applications. -
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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... -
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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. -
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
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PANDA
A comprehensive and flexible quantification tool for proteomics data
PANDA is a comprehensive and flexib tool for quantitative proteomics data analysis, which is developed based on our solid foundations in quantitative proteomics for years. Several novelties have been implemented in it. First, we implement the advantage algorithms of LFQuant (Proteomics 2012, 12, (23-24), 3475-84) and SILVER (Bioinformatics 2014, 30, (4), 586-7) into PANDA. Second, we consider the state-of-art concept of quantification reliability in this quantitative workflow. On the levels... -
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LEACrypt
TTAK.KO-12.0223 Lightweight Encryption Algorithm Tool
The Lightweight Encryption Algorithm (also known as LEA) is a 128-bit block cipher developed by South Korea in 2013 to provide confidentiality in high-speed environments such as big data and cloud computing, as well as lightweight environments such as IoT devices and mobile devices. LEA is one of the cryptographic algorithms approved by the Korean Cryptographic Module Validation Program (KCMVP) and is the national standard of Republic of Korea (KS X 3246). LEA is included in the ISO/IEC 29192-2:2019 standard (Information security - Lightweight cryptography - Part 2: Block ciphers). ... -
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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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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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X10
Performance and Productivity at Scale
...With these, APGAS can express both regular and irregular parallelism, message-passing-style and active-message-style computations, fork-join and bulk-synchronous parallelism. Both its modern, type-safe sequential core and simple programming model for concurrency and distribution contribute to making X10 a high-productivity language in the HPC and Big Data spaces. User productivity is further enhanced by providing tools such as an Eclipse-based IDE (X10DT). Implementations of X10 are available for a wide variety of hardware and software platforms ranging from laptops, to commodity clusters, to supercomputers. -
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Vaex
Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python
Data science solutions, insights, dashboards, machine learning, deployment. We start at 100GB. Vaex is a high-performance Python library for lazy Out-of-Core data frames (similar to Pandas), to visualize and explore big tabular datasets. It calculates statistics such as mean, sum, count, standard deviation etc, on an N-dimensional grid for more than a billion (10^9) samples/rows per second. Visualization is done using histograms, density plots and 3d volume rendering, allowing interactive exploration of big data. ... -
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PROPER is a package for visual evaluation of ranking classifiers for biological big data mining studies in the mathematical language MATLAB. 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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PROPER is a package for visual evaluation of ranking classifiers for biological big data mining studies in the mathematical language MATLAB. 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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Chordalysis
Log-linear analysis (data modelling) for high-dimensional data
===== Project moved to https://github.com/fpetitjean/Chordalysis ===== Log-linear analysis is the statistical method used to capture multi-way relationships between variables. However, due to its exponential nature, previous approaches did not allow scale-up to more than a dozen variables. We present here Chordalysis, a log-linear analysis method for big data. Chordalysis exploits recent discoveries in graph theory by representing complex models as compositions of triangular structures,... -
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iOVFDT
iOVFDT algorithm of incremental decision tree
How to extract meaningful information from big data has been a popular open problem. Decision tree, which has a high degree of knowledge interpretation, has been favored in many real world applications. However noisy values commonly exist in high-speed data streams, e.g. real-time online data feeds that are prone to interference. When processing big data, it is hard to implement pre-processing and sampling in full batches. To solve this trade-off, we propose a new decision tree so called incrementally optimized very fast decision tree (iOVFDT). ... -
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MapReduce Brazil
Aggregates MapReduce projects
Nowadays the production and storage of Big Data is common, both in the academy and in the enterprises. To process this huge amount of data it is essential the use of high performance platforms and programming models like MapReduce
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