Open Source Go Database Software
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Go Database Software
View 472 business solutionsBrowse free open source Go Database Software and projects below. Use the toggles on the left to filter open source Go Database Software by OS, license, language, programming language, and project status.
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Gemini 3 and 200+ AI Models on One PlatformBuild, govern, and optimize agents and models with Gemini Enterprise Agent Platform.
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Full-stack observability with actually useful AI | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
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PocketBase
Open Source realtime backend in 1 file
PocketBase is an open-source backend written in Go, packaged as a single binary. It features an embedded SQLite database, real-time subscriptions, built-in authentication and file management, a web-based admin dashboard, and a simple REST-style API—ideal for building self‑contained apps on a single server. -
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Grafana
Leading open-source visualization and observability platform
Grafana OSS is the leading open-source platform for visualization and observability. It enables teams to query, visualize, alert on, and explore telemetry data from multiple sources in a single interface. With support for 100+ data source plugins—including Prometheus, Loki, Elasticsearch, InfluxDB, SQL/NoSQL databases, and OpenTelemetry—Grafana helps teams correlate metrics, logs, and traces across applications and infrastructure. Users can build interactive dashboards with rich visualizations, template variables, and reusable panels to monitor systems and troubleshoot issues in real time. Grafana includes capabilities such as ad hoc data exploration, alerting, annotations, and flexible query support. Its extensible plugin ecosystem integrates with cloud platforms, databases, and developer tools—allowing teams to build observability workflows without vendor lock-in. The easiest way to get started with Grafana is with Grafana Cloud, our fully managed, full-stack observability platform. -
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InfluxDB
The open source time series database
InfluxDB is an open source time series datastore designed to handle high write and query loads. 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/ -
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OWASP Amass
In-depth attack surface mapping and asset discovery
The OWASP Amass Project has developed a tool to help information security professionals perform network mapping of attack surfaces and perform external asset discovery using open source information gathering and active reconnaissance techniques. The Open Web Application Security Project (OWASP) is a nonprofit foundation that works to improve the security of software. All of our projects ,tools, documents, forums, and chapters are free and open to anyone interested in improving application security. The volume argument allows the Amass graph database to persist between executions and output files to be accessed on the host system. The first field (left of the colon) of the volume option is the amass output directory that is external to Docker, while the second field is the path, internal to Docker, where amass will write the output files. -
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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Prometheus
Open source monitoring system and time series database
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. -
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Dolt
Dolt, it's Git for data
Dolt is a SQL database that you can fork, clone, branch, merge, push and pull just like a git repository. Connect to Dolt just like any MySQL database to run queries or update the data using SQL commands. Use the command line interface to import CSV files, commit your changes, push them to a remote, or merge your teammate's changes. All the commands you know for Git work exactly the same for Dolt. Git versions files, Dolt versions tables. It's like Git and MySQL had a baby. We also built DoltHub, a place to share Dolt databases. We host public data for free. If you want to host your own version of DoltHub, we have DoltLab. If you want us to run a Dolt server for you, we have Hosted Dolt. MySQL comes with a MySQL server called mysqld and a MySQL client called mysql. You're only interested in the client. After following the instructions from MySQL's documentation, make sure you have a copy of the mysql client on your path. -
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CockroachDB
The open source, cloud-native SQL database
CockroachDB is an SQL database designed for global cloud services. It delivers resilient, consistent, distributed SQL at your scale thanks in large part to its unique self-organizing and self-healing architecture. It is able to scale horizontally, survive all kinds of failures with minimal latency disruption and zero manual intervention, and supports strongly-consistent ACID transactions. All this while providing a familiar SQL API. -
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WAL-G
Archival and Restoration for databases in the Cloud
WAL-G is an archival restoration tool for PostgreSQL, MySQL/MariaDB, and MS SQL Server (beta for MongoDB and Redis). WAL-G is the successor of WAL-E with a number of key differences. WAL-G uses LZ4, LZMA, ZSTD, or Brotli compression, multiple processors, and non-exclusive base backups for Postgres. More information on the original design and implementation of WAL-G can be found on the Citus Data blog post "Introducing WAL-G by Citus: Faster Disaster Recovery for Postgres". A precompiled binary for Linux AMD 64 of the latest version of WAL-G can be obtained under the Releases tab. To configure the compression method used for backups. Possible options are lz4, lzma, zstd, brotli. The default method is lz4. LZ4 is the fastest method, but the compression ratio is bad. LZMA is way much slower. However, it compresses backups about 6 times better than LZ4. Brotli and zstd are a good trade-off between speed and compression ratio, which is about 3 times better than LZ4. -
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rqlite
The lightweight, distributed relational database built on SQLite
rqlite is an easy-to-use, lightweight, distributed relational database, which uses SQLite as its storage engine. rqlite is simple to deploy, operating it is very straightforward, and its clustering capabilities provide you with fault-tolerance and high availability. rqlite is available for Linux, macOS, and Microsoft Windows. rqlite gives you the functionality of a rock solid, fault-tolerant, replicated relational database, but with very easy installation, deployment, and operation. With it you've got a lightweight and reliable distributed relational data store. Think etcd or Consul, but with relational data modeling also available. You could use rqlite as part of a larger system, as a central store for some critical relational data, without having to run larger, more complex distributed databases. rqlite uses Raft to achieve consensus across all the instances of the SQLite databases, ensuring that every change made to the system is made to a quorum of SQLite databases. -
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immudb
Immutable database based on zero trust, SQL and Key-Value, tamperproof
immudb is a database with built-in cryptographic proof and verification. It tracks changes in sensitive data and the integrity of the history will be protected by the clients, without the need to trust the database. It can operate both as a key-value store, and/or as a relational database (SQL). Traditional database transactions and logs are mutable, and therefore there is no way to know for sure if your data has been compromised. immudb is immutable. You can add new versions of existing records, but never change or delete records. This lets you store critical data without fear of it being tampered with. Data stored in immudb is cryptographically coherent and verifiable. Unlike blockchains, immudb can handle millions of transactions per second, and can be used both as a lightweight service or embedded in your application as a library. immudb runs everywhere, on an IoT device, your notebook, a server, on-premise or in the cloud. -
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BadgerDB
Fast key-value DB in Go
BadgerDB is an embeddable, persistent and fast key-value (KV) database written in pure Go. It is the underlying database for Dgraph, a fast, distributed graph database. It's meant to be a performant alternative to non-Go-based key-value stores like RocksDB. Badger is stable and is being used to serve data sets worth hundreds of terabytes. Badger supports concurrent ACID transactions with serializable snapshot isolation (SSI) guarantees. A Jepsen-style bank test runs nightly for 8h, with --race flag and ensures the maintenance of transactional guarantees. Badger has also been tested to work with filesystem-level anomalies, to ensure persistence and consistency. Badger is being used by a number of projects including Dgraph, Jaeger Tracing, UsenetExpress, and many more. BadgerDB is a pretty special package from the point of view that the most important change we can make to it is not on its API but rather on how data is stored on disk. -
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Beats
Lightweight data shippers of the Elastic Stack
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. -
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Bytebase
The GitHub/GitLab for database DevSecOps
The GitHub/GitLab for database DevSecOps. World's most advanced database DevSecOps solution for Developer, Security, DBA and Platform Engineering teams. -
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Cloud SQL Auth Proxy
A utility for connecting securely to your Cloud SQL instances
Cloud SQL Proxy is a secure connectivity utility that enables applications to connect to Google Cloud SQL instances without requiring manual configuration of SSL certificates or network access rules. It works by establishing an encrypted connection between the client and the Cloud SQL instance using TLS and authenticating requests through Google Cloud IAM, ensuring that only authorized users or services can access the database. The proxy runs locally or alongside applications, exposing a local TCP port or Unix socket that applications can use as if they were connecting to a standard database. This abstraction simplifies development and deployment by allowing developers to use familiar database clients while the proxy handles authentication and encryption behind the scenes. It supports both public and private IP connections and can be deployed in environments such as local machines, virtual machines, Kubernetes clusters, or as a sidecar container. -
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Dgraph
The Only Native GraphQL Database With A Graph Backend
Dgraph is a horizontally scalable and distributed GraphQL database, the only native GraphQL database to have a graph backend. Dgraph is able to do things that other graph DBs can’t. It provides consistent replication, automatic data movement for shard balancing, distributed ACID transactions, as well as native support for full text search, regular expressions and geo search. If you have over 10 SQL tables interconnected via foreign keys, or sparse data that don’t fit neatly into SQL tables; or if you just want a simple and flexible schema, and prioritize speed and performance at scale, Dgraph is the best choice for you. It’s fully equipped with everything you need and more. -
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Cortex
A horizontally scalable, multi-tenant, long term Prometheus
Horizontally scalable, highly available, multi-tenant, long-term storage for Prometheus. Durably store data for longer than the lifetime of any single machine, and use this data for long-term capacity planning. Cortex makes your PromQL queries blazin' fast through aggressive parallelization and caching. Cortex gives you a global view of Prometheus time series data that includes data in long-term storage, greatly expanding the usefulness of PromQL for analytical purposes. Cortex runs across multiple machines in a cluster, exceeding the throughput and storage of a single machine. This enables you to send the metrics from multiple Prometheus servers to a single Cortex cluster. -
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Dbmate
A lightweight, framework-agnostic database migration tool
Dbmate is a database migration tool, to keep your database schema in sync across multiple developers and your production servers. It is a standalone command line tool, which can be used with Go, Node.js, Python, Ruby, PHP, or any other language or framework you are using to write database-backed applications. This is especially helpful if you are writing many services in different languages, and want to maintain some sanity with consistent development tools. Supports MySQL, PostgreSQL, SQLite, and ClickHouse. Uses plain SQL for writing schema migrations. Migrations are timestamp-versioned, to avoid version number conflicts with multiple developers. Migrations are run atomically inside a transaction. Supports creating and dropping databases (handy in development/test). Supports saving a schema.sql file to easily diff schema changes in git. Database connection URL is defined using an environment variable (DATABASE_URL by default), or specified on the command line. -
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SQL Exporter
Database agnostic SQL exporter for Prometheus
SQL Exporter is a configuration-driven exporter that exposes metrics gathered from DBMSs, for use by the Prometheus monitoring system. Out of the box, it provides support for MySQL, PostgreSQL, Microsoft SQL Server, and Clickhouse, but any DBMS for which a Go driver is available may be monitored after rebuilding the binary with the DBMS driver included. The collected metrics and the queries that produce them are entirely configuration-defined. SQL queries are grouped into collectors -- logical groups of queries, e.g., query stats or I/O stats, mapped to the metrics they populate. Collectors may be DBMS-specific (e.g,. MySQL InnoDB stats) or custom, deployment-specific (e.g., pricing data freshness). This means you can quickly and easily set up custom collectors to measure data quality, whatever that might mean in your specific case. -
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VictoriaMetrics
VictoriaMetrics: fast, cost-effective monitoring solution
VictoriaMetrics is a fast, cost-effective and scalable monitoring solution and time series database. VictoriaMetrics is available in binary releases, Docker images, Snap packages and source code. Just download the latest version of VictoriaMetrics. VictoriaMetrics is developed at a fast pace, so it is recommended periodically checking the CHANGELOG and performing regular upgrades. It can be used as long-term storage for Prometheus. See these docs for details. It can be used as a drop-in replacement for Prometheus in Grafana, because it supports Prometheus querying API. It can be used as a drop-in replacement for Graphite in Grafana, because it supports Graphite API. It features easy setup and operation. VictoriaMetrics consists of a single small executable without external dependencies. All the configuration is done via explicit command-line flags with reasonable defaults. All the data is stored in a single directory pointed by -storageDataPath command-line flag. -
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spicedb
Open Source, Google Zanzibar-inspired permissions database
SpiceDB is a graph database purpose-built for storing and evaluating access control data. As of 2021, broken access control became the #1 threat to the web. With SpiceDB, developers finally have the solution to stopping this threat the same way as the hyperscalers. Open Source, Google Zanzibar-inspired permissions database to enable fine-grained access control for customer applications. Building modern authorization from scratch is non-trivial and requires years of development from domain experts. Until SpiceDB, the only developers with access to these workflows were employed by massive tech companies that could invest in building mature, but proprietary solutions. Now we have a community organized around sharing this technology so that the entire industry can benefit. -
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sqldef
Idempotent schema management for MySQL, PostgreSQL, and more
sqldef is a schema migration tool that automatically generates SQL migration statements by comparing database schemas. Instead of writing migrations manually, developers define the desired schema, and sqldef computes the difference. It's compatible with MySQL, PostgreSQL, SQLite, and others, making migrations safer and more maintainable. -
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Bolt
An embedded key/value database for Go
Bolt is a pure Go key/value store inspired by Howard Chu's LMDB project. The goal of the project is to provide a simple, fast, and reliable database for projects that don't require a full database server such as Postgres or MySQL. Since Bolt is meant to be used as such a low-level piece of functionality, simplicity is key. The API will be small and only focus on getting values and setting values. That's it. Bolt is stable, the API is fixed, and the file format is fixed. Full unit test coverage and randomized black box testing are used to ensure database consistency and thread safety. Bolt is currently used in high-load production environments serving databases as large as 1TB. Many companies such as Shopify and Heroku use Bolt-backed services every day. Please note that Bolt obtains a file lock on the data file so multiple processes cannot open the same database at the same time. -
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Genji
Document-oriented, embedded SQL database
Genji is an embedded database written in Go that aims to simplify dealing with data in the modern world. It combines the power of SQL with the versatility of documents to provide a maximum of flexibility with no compromise. Run powerful queries on rich documents with an expressive SQL syntax. Create tables with strict schemas, partial schemas, or no schemas at all to control your data the way you want it. Fully serializable transactions, in-memory mode, memory usage control, and more. Genji was designed for simplicity in mind. It is really easy to insert and read documents of any shape. Genji mixes the best of both worlds by combining powerful SQL commands with JSON. Genji tables are schemaless, but it is possible to add constraints on any field to ensure the coherence of data within a table. -
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Go MySQL Driver
MySQL driver for Go's (golang) database/sql package
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. -
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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.
