Open Source Go System Software

Grafana OSS is a leading open-source visualization and observability platform that lets you query, visualize, alert on, and explore your data—regardless of where it’s stored. With support for 100+ data source plugins (such as Prometheus, Loki, Elasticsearch, InfluxDB, SQL/NoSQL databases, OTel, and more), you can unify metrics, logs, traces, and other observability signals in one place. Grafana OSS empowers you to build dynamic, reusable dashboards with rich visualizations, template variables, interactive filtering, and cross-panel linking. Its Explore mode enables ad-hoc queries and side-by-side comparisons of time ranges, queries, and data sources. Grafana also includes built-in alerting, allowing you to define threshold-based rules and send notifications to external systems (e.g. Slack, PagerDuty, OpsGenie). Backed by a strong community (https://grafana.com/community/) and open governance, Grafana OSS is free to use, modify, and deploy under the AGPL-3.0 license.

Prometheus is a leading open source systems and service monitoring solution. It works by collecting metrics from configured targets at given intervals, evaluating rule expressions, and then displaying the results. It can also signal an alert if a condition is observed to be true. What sets Prometheus apart from other monitoring systems is its highly dimensional data model, powerful query language, autonomous single server nodes, among many other distinguishing features. It also offers several client libraries for easy instrumentation of services, as well as many integration options.

Beats is a platform of lightweight, single-use data shippers written in Go. It captures all sorts of operational data from hundreds or thousands of machines and systems and sends them to Logstash or Elasticsearch. Beats is lightweight in that it has a small installation footprint, uses limited system resources and has no runtime dependencies. It consists of: Auditbeat (for audit data), Filebeat (for log files), Functionbeat (serverless shipper), Heartbeat (for uptime monitoring), Metricbeat (for metrics), Packetbeat (for monitoring network data), and Winlogbeat (for Windows Event logs), with many other Beats created by the community.

Golang SQL database client for ClickHouse. There are two version of this client, v1 and v2, available as separate branches. v1 is now in a state of maintenance, we will only accept PRs for bug and security fixes. Uses ClickHouse native format for optimal performance. Utilizes low level ch-go client for encoding/decoding and compression (versions >= 2.3.0). Supports native ClickHouse TCP client-server protocol. Compatibility with database/sql (slower than native interface!). Database/sql supports http protocol for transport. (Experimental). Marshal rows into structs (ScanStruct, Select). Unmarshal struct to row (AppendStruct). Connection pool Failover and load balancing. Bulk write support (for database/sql use begin->prepare->(in loop exec)->commit). AsyncInsert, named and numeric placeholders support. LZ4/ZSTD compression support. External data.

Lightweight and fast, native Go implementation. No C-bindings, just pure Go. Connections over TCP/IPv4, TCP/IPv6, Unix domain sockets or custom protocols. Automatic handling of broken connections, as well as automatic Connection Pooling (by database/sql package). Supports queries larger than 16MB. Full sql.RawBytes support. It provides intelligent LONG DATA handling in prepared statements. Secure LOAD DATA LOCAL INFILE support with file allowlisting and io.Reader support. Optional time.Time parsing, as well as optional placeholder interpolation. db.SetConnMaxLifetime() is required to ensure connections are closed by the driver safely before connection is closed by MySQL server, OS, or other middlewares. Since some middlewares close idle connections by 5 minutes, we recommend timeout shorter than 5 minutes. This setting helps load balancing and changing system variables too.

redix is a very simple key => value storage engine that speaks redis and even more simpler and flexible. redis is very simple, sometimes we abuse it, so I decided to build a pure key-value storage system that introduces the core utilities for building any data structure you want based on the key => value model that is because I think that everything could be modeled easily using that model, so I decided to not to follow redis and all of its commands, you won’t find lpush, hset, sadd, … etc you will find a new way to do the same job but more easier and flexable, i.e, the well-known hset key field value command could be replaced with set key/field value, but sometimes you need to return a specific hashmap as key => value, but you run hget key field to get the key’s value and also it could be replaced with get key/field, but how could we replace hgetall key? I will say “it is easy”, let’s make the hget command work as a prefix scanner that scan the whole database.

SummitDB is an in-memory, NoSQL key/value database. It persists to disk, uses the Raft consensus algorithm, is ACID compliant, and is built on a transactional and strongly-consistent model. It supports custom indexes, geospatial data, JSON documents, and user-defined JS scripting. The easiest way to get SummitDB is to use one of the pre-built release binaries which are available for OSX, Linux, and Windows. SummitDB can be compiled and used on Linux, OSX, Windows, FreeBSD, ARM (Raspberry PI) and probably others since the codebase is 100% Go. We support both 32-bit and 64-bit systems. Go must be installed on the build machine. It may be worth noting that while SummitDB supports many Redis features, it is not a strict Redis clone. SummitDB provides one key space that is a large B-tree. An ordered key space allows for stable paging through keys using the KEYS command. Redis uses an unordered dictionary structure and provides a specialized SCAN command for iterating through keys.

Open Source AI-ready PaaS and framework for building your own cloud on bare metal and running managed Kubernetes, virtual machines, Databases-as-a-Service or for creating your own AWS/GCP/Azure competitor for ISP/MSP/hosting providers. CNCF Project - Control your data - Cut dependence from the tech giants - Enable digital sovereignty - Use modern tools and APIs with any server - Fully utilize GPU resources for AI Who is it for? Banks and fintechs, AI-driven companies, service providers and data centers, governances, regulated and privacy-conscious organizations, integrators and independent IT consultants

In most cases clients will use the database/sql package instead of using this package directly. Similarly to libpq, when establishing a connection using pq you are expected to supply a connection string containing zero or more parameters. A subset of the connection parameters supported by libpq are also supported by pq. Additionally, pq also lets you specify run-time parameters (such as search_path or work_mem) directly in the connection string. This is different from libpq, which does not allow run-time parameters in the connection string, instead requiring you to supply them in the options parameter. database/sql does not dictate any specific format for parameter markers in query strings, and pq uses the Postgres-native ordinal markers. For additional instructions on querying see the documentation for the database/sql package.