Search Results for "data processing"
Sort By:
Showing 56 open source projects for "data processing"
View related business solutions-
$300 in Free Credit Towards Top Cloud ServicesStart your project in minutes. After credits run out, 20+ products include free monthly usage. Only pay when you're ready to scale.
-
Earn up to 16% annual interest with Nexo.Generate interest, borrow against your crypto, and trade a range of cryptocurrencies — all in one platform. Geographic restrictions, eligibility, and terms apply.
-
1
Kapacitor
Open source framework for processing, monitoring, and alerting
Open source framework for processing, monitoring, and alerting on time series data. Kapacitor is a real-time data processing engine for monitoring and alerting, specifically designed to work with time-series data from InfluxDB. -
2
pdfcpu
A PDF processor written in Go
pdfcpu is a PDF processing library written in Go supporting encryption. It provides both an API and a CLI. Supported are all versions up to PDF 1.7 (ISO-32000). This is an effort to build a comprehensive PDF processing library from the ground up written in Go. Over time pdfcpu aims to support the standard range of PDF processing features and also any interesting use cases that may present themselves along the way. The main focus lies on strong support for batch processing and scripting via a... -
3
go-streams
A lightweight stream processing library for Go
A lightweight stream processing library for Go. go-streams provides a simple and concise DSL to build data pipelines. In computing, a pipeline, also known as a data pipeline, is a set of data processing elements connected in series, where the output of one element is the input of the next one. The elements of a pipeline are often executed in parallel or in time-sliced fashion. -
4
Numaflow
Kubernetes-native platform to run massively parallel data/streaming
Numaflow is a Kubernetes-native tool for running massively parallel stream processing. A Numaflow Pipeline is implemented as a Kubernetes custom resource and consists of one or more source, data processing, and sink vertices. Numaflow installs in a few minutes and is easier and cheaper to use for simple data processing applications than a full-featured stream processing platform. -
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.
-
5
Pachyderm
Data-Centric Pipelines and Data Versioning
...Pachyderm provides a powerful solution to optimize data processing, MLOps, and ML Lifecycles. -
6
Miller
Miller is like awk, sed, cut, join, and sort for name-indexed data
Miller is like awk, sed, cut, join, and sort for data formats such as CSV, TSV, JSON, JSON Lines, and positionally-indexed. With Miller, you get to use named fields without needing to count positional indices, using familiar formats such as CSV, TSV, JSON, JSON Lines, and positionally-indexed. Then, on the fly, you can add new fields which are functions of existing fields, drop fields, sort, aggregate statistically, pretty-print, and more. Miller operates on key-value-pair data while the... -
7
InfluxDB
The open source time series database
...Time series is currently the fastest growing database category there is, and InfluxDB is here to ensure businesses can keep up. InfluxDB provides infrastructure and application monitoring, IoT monitoring and analytics and more. It has APIs for storing and querying data, processing it in the background for ETL or monitoring and alerting purposes. This data can also be visualized, explored and more to help businesses seize opportunities and make the best decisions. InfluxDB is easy to start and easy to scale. Learn more about it on https://www.influxdata.com/ -
8
Benthos
Fancy stream processing made operationally mundane
Benthos is a high performance and resilient stream processor, able to connect various sources and sinks in a range of brokering patterns and perform hydration, enrichments, transformations and filters on payloads. It comes with a powerful mapping language, is easy to deploy and monitor, and ready to drop into your pipeline either as a static binary, docker image, or serverless function, making it cloud native as heck. Delivery guarantees can be a dodgy subject. Benthos processes and... -
9
SigLens
100x Efficient Log Management than Splunk
Siglens is an open-source signal analysis toolkit designed for processing and visualizing time-series data, commonly used in scientific and engineering applications. -
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
-
10
Nuclio
High-Performance Serverless event and data processing platform
Nuclio is an open source and managed serverless platform used to minimize development and maintenance overhead and automate the deployment of data-science-based applications. Real-time performance running up to 400,000 function invocations per second. Portable across low laptops, edge, on-prem and multi-cloud deployments. The first serverless platform supporting GPUs for optimized utilization and sharing. Automated deployment to production in a few clicks from Jupyter notebook. Deploy one of... -
11
Hacks
A collection of hacks and one-off scripts
Hacks is a collection of experimental scripts, utilities, and one-off tools created to solve specific problems in security research, data processing, and automation. Rather than being a single cohesive application, it serves as a repository of practical command-line tools that can be used independently or combined into workflows. The scripts cover a wide range of tasks, including URL manipulation, parameter replacement, data extraction, and reconnaissance automation. ... -
12
Watermill
Building event-driven applications the easy way in Go
Go library for building event-driven applications. Our goal was to create a tool that is easy to understand, even by junior developers. It doesn't matter if you want to do Event-driven architecture, CQRS, Event Sourcing or just stream MySQL Binlog to Kafka. Watermill was designed to process hundreds of thousands of messages per second. Every component is built in a way that allows you to configure it for your needs. You can also implement your own middleware for the router. Watermill is... -
13
Neuroglancer
WebGL-based viewer for volumetric data
...The viewer is built with a multi-threaded architecture, separating rendering and data processing to ensure smooth performance even with massive datasets. Extensively used in neuroscience research, Neuroglancer supports integration with tools. -
14
ojg
Optimized JSON for Go
Optimized JSON for Go is a high-performance parser with a variety of additional JSON tools. OjG is optimized to processing huge data sets where data does not necessarily conform to a fixed structure. -
15
Bitalosdb
Bitalosdb is a high-performance KV storage engine
BitalosDB is a distributed, high-performance key-value database designed for cloud-native applications. It is optimized for scalability, supporting large workloads while maintaining low latency and high availability. -
16
paperless-gpt
Use LLMs and LLM Vision (OCR) to handle paperless-ngx
paperless-gpt is an AI-powered extension for document management systems that enhances the capabilities of paperless-ngx by integrating large language models and vision-based OCR to automate document processing and organization. It is designed to transform scanned or uploaded documents into structured, searchable, and intelligently categorized data without requiring manual tagging or sorting. The system uses OCR combined with LLM reasoning to extract text, classify documents, and generate metadata such as tags, titles, and categories automatically. ... -
17
encoding
Go package containing implementations of efficient encoding
Go package containing implementations of encoders and decoders for various data formats. At Segment, we do a lot of marshaling and unmarshaling of data when sending, queuing, or storing messages. The resources we need to provision on the infrastructure are directly related to the type and amount of data that we are processing. At the scale we operate at, the tools we choose to build programs can have a large impact on the efficiency of our systems. -
18
ASNmap
CLI tool for mapping organization network ranges using ASN data
...Output can be generated in multiple formats including plain text, JSON, and CSV, enabling flexible data processing and analysis. asnmap also supports reading input from standard input and piping its results directly into other command line tools for chained workflows. -
19
Grafana Agent
Vendor-neutral programmable observability pipelines
Grafana Agent is an OpenTelemetry Collector distribution with a configuration inspired by Terraform. It is designed to be flexible, performant, and compatible with multiple ecosystems such as Prometheus and OpenTelemetry. Grafana Agent is based on components. Components are wired together to form programmable observability pipelines for telemetry collection, processing, and delivery. -
20
memphis
Next-Generation Event Processing Platform
Memphis enables building modern queue-based applications that require large volumes of streamed and enriched data, modern protocols, zero ops, up to x9 faster development, up to x46 fewer costs, and significantly lower dev time for data-oriented developers and data engineers. Queues and brokers are a mission-critical component in the modern application architecture and should be highly available and stable as possible. Provide great performance while maintaining efficient resource... -
21
Bacalhau
Community-driven, simple, yet powerful framework
Bacalhau is a decentralized compute platform for running jobs on data stored across distributed networks, like IPFS or Filecoin, without moving the data to centralized cloud environments. It allows developers to run containerized workloads close to where the data lives, reducing latency, cost, and privacy risks. Bacalhau supports various runtime environments and is designed to make decentralized data processing as accessible as traditional cloud computing. ... -
22
getty
Asynchronous network I/O library
Getty is an asynchronous network I/O library developed in Golang. It operates on TCP, UDP, and WebSocket network protocols, providing a consistent interface EventListener. Within Getty, each connection (session) involves two separate goroutines. One handles the reading of TCP streams, UDP packets, or WebSocket packages, while the other manages the logic processing and writes responses into the network write buffer. If your logic processing might take a considerable amount of time, it's... -
23
XLSX
Go (golang) library for reading and writing XLSX files
...These can be used to modify the behavior of the resultant struct, in particular they replace the `…WithRowLimit` variants of those methods with the result of calling `xlsx.RowLimit` and they add the ability to define a custom backing store for the spreadsheet data to be held in whilst processing. The full API docs can be viewed using go’s built in documentation tool. -
24
Memobase
Fast backend for long-term AI user memory via structured profiles
Memobase is an open source backend system that enables long-term user memory functionality for AI applications by capturing and structuring information about users across interactions. Its design centers on creating user profiles and recording event timelines, allowing AI systems to remember, understand, and evolve in their behaviour toward individual users over time. Instead of relying purely on traditional embedding-based retrieval or RAG systems, Memobase uses profile and timeline... -
25
Colly
Elegant Scraper and Crawler Framework for Golang
Colly provides a clean interface to write any kind of crawler/scraper/spider. With Colly you can easily extract structured data from websites, which can be used for a wide range of applications, like data mining, data processing or archiving. Clean API. Fast (>1k request/sec on a single core) Manages request delays and maximum concurrency per domain. Automatic cookie and session handling. Sync/async/parallel scraping. Distributed scraping. Caching, automatic encoding of non-unicode responses. ...
