Open Source Go Data Management Systems
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Go Data Management Systems
View 4254 business solutionsBrowse free open source Go Data Management Systems and projects below. Use the toggles on the left to filter open source Go Data Management Systems by OS, license, language, programming language, and project status.
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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 the example serverless functions or write your own. The dashboard, when running outside an orchestration platform (e.g. Kubernetes or Swarm), will simply be deployed to the local docker daemon. The Getting Started With Nuclio On Kubernetes guide has a complete step-by-step guide to using Nuclio serverless functions over Kubernetes. -
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Conduit
Conduit streams data between data stores. Kafka Connect replacement
Conduit is a data streaming tool written in Go. It aims to provide the best user experience for building and running real-time data pipelines. Conduit comes with batteries included, it provides a UI, common connectors, processors and observability data out of the box. Sync data between your production systems using an extensible, event-first experience with minimal dependencies that fit within your existing workflow. Eliminate the multi-step process you go through today. Just download the binary and start building. Conduit connectors give you the ability to pull and push data to any production datastore you need. If a datastore is missing, the simple SDK allows you to extend Conduit where you need it. Conduit pipelines listen for changes to a database, data warehouse, etc., and allows your data applications to act upon those changes in real-time. Run it in a way that works for you; use it as a standalone service or orchestrate it within your infrastructure. -
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Arcane
Modern Docker Management, Designed for Everyone
Arcane is a modern, open-source Docker management platform crafted to simplify container orchestration and service operations with an intuitive interface and broad tooling support. Aimed at developers, sysadmins, and self-hosters alike, Arcane combines both graphical and command-line experiences for discovering, launching, and managing containers, images, networks, and volumes across local and remote environments. It emphasizes usability and accessibility, making it less intimidating than traditional tools like Portainer while still powerful enough for real-world usage, including logs, metrics, and console access for individual containers. The project integrates frontend and backend components that work together to provide a cohesive environment management experience, often packaged to run alongside Docker and Docker Compose setups with minimal configuration. -
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CloudQuery
The open-source cloud asset inventory powered by SQL
CloudQuery extracts, transforms and loads your cloud assets into normalized PostgreSQL tables. CloudQuery enables you to assess, audit, and monitor the configurations of your cloud assets. Use standard SQL to find any asset based on any configuration or relation to other assets. Connect CloudQuery standard PostgreSQL database to your favorite BI/Visualization tool such as Grafana, QuickSight, etc. Codify your security & compliance rules with SQL as the query engine. Integrate CloudQuery with your current visualization, monitoring, and alerting such as Grafana. CloudQuery supports the TimescaleDB PostgreSQL extension, giving you full historical snapshots of your cloud asset inventory. Data analysis, security, auditing, and compliance. Leverage SQL to get visibility into your cloud infrastructure and SaaS applications. Build a cloud-asset inventory across any of our supported official or community providers. -
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AQUATONE
A tool for domain flyovers
Aquatone is a tool for visual inspection of websites across a large amount of hosts and is convenient for quickly gaining an overview of HTTP-based attack surface. Aquatone is designed to be as easy to use as possible and to integrate with your existing toolset with no or minimal glue. Aquatone is started by piping output of a command into the tool. It doesn't really care how the piped data looks as URLs, domains, and IP addresses will be extracted with regular expression pattern matching. This means that you can pretty much give it output of any tool you use for host discovery. Aquatone is now completely focused on screenshotting and reporting. I know a lot of people used Aquatone for its DNS enumeration capabilities and it was definitely very good at that when it was released. Now other tools are doing a much better job of this, so I decided to leave it out of the new Aquatone, and instead make it easy to use it with your tool of choice. -
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Kubernetes History Inspector
A log viewer for Kubernetes troubleshooting
The khi repository is a Google Cloud open-source project focused on infrastructure and system-level tooling, typically aimed at enabling advanced cloud-native workflows, observability, or orchestration in Kubernetes-based environments. It is designed to support engineers working with distributed systems by providing utilities and abstractions that simplify deployment, monitoring, or operational management. The project aligns with Google Cloud’s broader ecosystem of tools that help developers build scalable, containerized applications while maintaining visibility into system behavior. It often emphasizes integration with Kubernetes clusters, cloud-native APIs, and modern DevOps practices, allowing teams to manage complex workloads more efficiently. Although not a beginner-oriented repository, it provides valuable components and reference implementations for advanced users building production systems. -
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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 acknowledges messages using an in-process transaction model with no need for any disk persisted state, so when connecting to at-least-once sources and sinks it's able to guarantee at-least-once delivery even in the event of crashes, disk corruption, or other unexpected server faults. This behaviour is the default and free of caveats, which also makes deploying and scaling Benthos much simpler. -
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Gorse Recommender System Engine
An open source recommender system service written in Go
An open-source recommender system service written in Go. Recommend items from Popular, latest, user-based, item-based and collaborative filtering. Search the best recommendation model automatically in the background. Support horizontal scaling in the recommendation stage after single node training. Support Redis, MySQL, Postgres, MongoDB, and ClickHouse as its storage backend. Expose RESTful APIs for data CRUD and recommendation requests. Analyze online recommendation performance from recently inserted feedback. Provide GUI for data management, system monitoring, and cluster status checking. Gorse is an open-source recommendation system written in Go. Gorse aims to be a universal open-source recommender system that can be easily introduced into a wide variety of online services. By importing items, users and interaction data into Gorse, the system will automatically train models to generate recommendations for each user. -
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KubeRay
A toolkit to run Ray applications on Kubernetes
KubeRay is a powerful, open-source Kubernetes operator that simplifies the deployment and management of Ray applications on Kubernetes. It offers several key components. KubeRay core: This is the official, fully-maintained component of KubeRay that provides three custom resource definitions, RayCluster, RayJob, and RayService. These resources are designed to help you run a wide range of workloads with ease. -
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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. Schema-free multi-dimensional data model with Metric, Tags, and Fields; The LinQL is flexible yet handy for real-time data analytics. Horizontal scalable is made simple by adding more new broker and storage nodes without too much thinking and manual operations. And the tags-based sharding strategy resolves the hotspot problem. LinDB is designed to work under a Multi-Active IDCs cloud architecture. The compute layer of LinDB, called brokers, supports efficient Multi-IDCs aggregation query. -
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Milvus
Vector database for scalable similarity search and AI applications
Milvus is an open-source vector database built to power embedding similarity search and AI applications. Milvus makes unstructured data search more accessible, and provides a consistent user experience regardless of the deployment environment. Milvus 2.0 is a cloud-native vector database with storage and computation separated by design. All components in this refactored version of Milvus are stateless to enhance elasticity and flexibility. Average latency measured in milliseconds on trillion vector datasets. Rich APIs designed for data science workflows. Consistent user experience across laptop, local cluster, and cloud. Embed real-time search and analytics into virtually any application. Milvus’ built-in replication and failover/failback features ensure data and applications can maintain business continuity in the event of a disruption. Component-level scalability makes it possible to scale up and down on demand. -
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lakeFS
lakeFS - Git-like capabilities for your object storage
Increase data quality and reduce the painful cost of errors. Data engineering best practices using git-like operations on data. lakeFS is an open-source data version control for data lakes. It enables zero-copy Dev / Test isolated environments, continuous quality validation, atomic rollback on bad data, reproducibility, and more. Data is dynamic, it changes over time. Dealing with that without a data version control system is error-prone and labor-intensive. With lakeFS, your data lake is version controlled and you can easily time-travel between consistent snapshots of the lake. Easier ETL testing - test your ETLs on top of production data, in isolation, without copying anything. Safely experiment and test on full production data. Easily Collaborate on production data with your team. Automate data quality checks within data pipelines. -
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json-scada
A portable SCADA/IoT platform centered on the MongoDB database server.
Standard IT tools applied to SCADA/IoT (MongoDB, PostgreSQL/TimescaleDB,Node.js, C#, Golang, Grafana, etc.). MongoDB as the real-time core database, persistence layer, config store, SOE historian. Portability and interoperability over Linux, Windows, x86/64, ARM. Horizontal scalability, from a single computer to big clusters (MongoDB-sharding), Bare Metal, Docker containers, VM, cloud, or hybrid deployments. Unlimited tags, servers, and users. HTML5 Web interface. UTF-8/I18N. Protocols: IEC61850 Client, IEC60870-5-101/104 Client and Server, DNP3 Client, OPC-UA Client/Server, MQTT/Sparkplug-B, Telegraf (various data sources for monitoring like Modbus, SNMP, etc.) Github. project https://github.com/riclolsen/json-scada Requirements for Windows Installer: Windows 10/11 64 bits or Server 2016, Windows PowerShell. -
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Apache DevLake
Apache DevLake is an open-source dev data platform
Apache DevLake is an open-source dev data platform that ingests, analyzes, and visualizes the fragmented data from DevOps tools to extract insights for engineering excellence, developer experience, and community growth. Apache DevLake is designed for developer teams looking to make better sense of their development process and to bring a more data-driven approach to their own practices. You can ask Apache DevLake many questions regarding your development process. Just connect and query. Your Dev Data lives in many silos and tools. DevLake brings them all together to give you a complete view of your Software Development Life Cycle (SDLC). From DORA to scrum retros, DevLake implements metrics effortlessly with prebuilt dashboards supporting common frameworks and goals. DevLake fits teams of all shapes and sizes, and can be readily extended to support new data sources, metrics, and dashboards, with a flexible framework for data collection and transformation. -
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BDS
Blockchain data parsing and persisting results
JD Cloud Blockchain Data Service (BDS) is a real-time data aggregating, analyzing, and visualization service for chain-like unstructured data from all kinds of 3rd party Blockchains. Splitter is the key module of Blockchain Data Service (BDS) and provides data analysis capability. Splitter is responsible for consuming blockchain data from message queue (kafka) and inserting data into persistent data storage services (relational database, data warehouse, etc.) for further processing. Before compiling and running BDS, you must install go's compilation environment locally. -
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Blue Whale Configuration Platform
Blue Whale smart cloud configuration platform
Has accumulated experience in supporting hundreds of Tencent businesses, compatible with various complex system architectures, born in operation and maintenance, and proficient in operation and maintenance. From configuration management to job execution, task scheduling and monitoring self-healing, and then through operation and maintenance big data analysis to assist operational decision-making, it covers the full-cycle assurance management of business operations in a comprehensive manner. The open PaaS has a powerful development framework and scheduling engine, as well as a complete operation and maintenance development training system, which helps the rapid transformation and upgrading of operation and maintenance. Through the Blue Whale intelligent cloud system, it can help enterprises quickly realize the automation of basic operation and maintenance services, thereby accelerating the transformation of DevOps, realizing a tool culture, and maximizing operational efficiency. -
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ClickVisual
Log analytic and data visualize platform built on clickhouse
ClickVisual is a lightweight browser-based logs analytics and logs search platform for ClickHouse. -
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FLOGO
Simplify building efficient & modern serverless functions and apps
Project Flogo is an ultra-light, Go-based open source ecosystem for building event-driven apps. Event-driven, you say? Yup, the notion of triggers and actions are leveraged to process incoming events. An action, a common interface, exposes key capabilities such as application integration, stream processing, etc. All capabilities within the Flogo Ecosystem have a few things in common, they all process events (in a manner suitable for the specific purpose) and they all implement the action interface exposed by Flogo Core. Integration Flows Application Integration process engine with conditional branching and a visual development environment. A simple pipeline-based stream processing action with event joining capabilities across multiple triggers & aggregation over time windows. Microgateway pattern for conditional, content-based routing, JWT validation, rate limiting, circuit breaking and other common patterns. -
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Fluid
Fluid, elastic data abstraction and acceleration for BigData/AI apps
Fluid, elastic data abstraction and acceleration for BigData/AI applications in the cloud. Provide DataSet abstraction for underlying heterogeneous data sources with multidimensional management in a cloud environment. 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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JuiceFS
JuiceFS is a distributed POSIX file system built on top of Redis
A POSIX, HDFS and S3 compatible distributed file system for cloud. JuiceFS is designed to bring back the gold-old memories and experience of file systems in local disks to the cloud. JuiceFS is POSIX compliant and is fully compatible with HDFS and S3. Cloud app building or migrating, file sharing cross-geo and cross-cloud has become easier than ever before. Whether it's a public cloud, private cloud, or hybrid cloud, JuiceFS is available on any cloud of your choice and delivers flexibility, availability, scalability and strong consistency for your data-intensive applications. 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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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. -
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Karpor
World's most promising Kubernetes Visualization Tool
Karpor is Intelligence for Kubernetes. It brings advanced Search, Insight and AI to Kubernetes. It is essentially a Kubernetes Visualization Tool. With Karpor, you can gain crucial visibility into your Kubernetes clusters across any clouds. -
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Koito
Koito is a modern, themeable scrobbler
Koito is a lightweight, self-hostable collaborative knowledge base and note-taking platform designed to help teams and individuals capture, organize, and link ideas with the reliability of a local or private server rather than relying on managed SaaS tools. It combines concepts from wikis, Zettelkasten systems, and modern note apps by letting you create interconnected notes, bidirectional links, and structured collections that mirror how knowledge naturally grows. The interface supports markdown editing with live preview, tag management, and graph-style browsing so you can explore relationships between pages instead of treating documents as isolated files. Because Koito is self-hosted, you retain ownership of your data and can integrate authentication systems for team access control. It also includes collaboration features like real-time editing or change history, making it suitable for team documentation, research projects, and personal knowledge management alike. -
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Log4jScanner
A log4j vulnerability filesystem scanner and Go package
log4jscanner is a filesystem scanner and Go package that helps organizations quickly identify vulnerable Log4j components inside JARs and shaded dependencies. Instead of probing networks, it walks directories and archives, including nested JARs, to find version fingerprints and risky classes associated with the Log4Shell family of issues. The focus on static analysis makes it suitable for container images, build artifacts, and offline systems where active scanning isn’t feasible. Clear, machine-readable output allows the tool to plug into CI/CD checks and fleet-wide inventory jobs. For responders, it reduces time-to-visibility by surfacing exactly which paths and bundles require patching or remediation. It’s a pragmatic addition to defense-in-depth programs that need verifiable evidence of exposure without deploying agents. -
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Neuroglancer
WebGL-based viewer for volumetric data
Neuroglancer is a WebGL-based visualization tool designed for exploring large-scale volumetric and neuroimaging datasets directly in the browser. It allows users to interactively view arbitrary 2D and 3D cross-sections of volumetric data alongside 3D meshes and skeleton models, enabling precise examination of neural structures and biological imaging results. Its multi-pane interface synchronizes multiple orthogonal views with a central 3D viewport, making it ideal for analyzing complex brain imaging data such as connectomics datasets. Neuroglancer operates entirely client-side, fetching data over HTTP in a variety of supported formats including Neuroglancer precomputed, N5, Zarr, and NIfTI, among others. 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.
