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The server is a **FastAPI application** served by Uvicorn, one process and one database for the core: every experiment run, parameter, metric, and model version lands in PostgreSQL through the same REST API every MLflow client already speaks.\n\nArtifacts are **a second store you choose**. Models, plots, and environment snapshots go to the artifact store you point at: local disk for a single server, or any S3-compatible object store for durability. The model registry, with versions, aliases, and lineage, is part of the same server.\n\nManaged MLflow exists inside other platforms: Databricks runs it as part of its lakehouse, and Amazon SageMaker offers hosted tracking servers billed by the hour. A self-hosted MLflow is **the open standard** the whole ML ecosystem integrates with, one server process with nothing metered.\n\nThe trade is the platform's spartan design. MLflow's built-in basic auth covers users and per-experiment permissions, but HTTPS, SSO, and backups are yours to wire up, the UI is minimal next to hosted tracking platforms, and model serving needs its own stack on top. Teams that want a fuller team platform should compare Weights & Biases Self-Hosted.",[11,12,13,14,15],"MLflow tracking server, a FastAPI application, from a single Docker image or pip install","PostgreSQL backend store for runs, parameters, metrics, and the model registry","Artifact storage on local disk or any S3-compatible object store","The model registry, with stages, versions, and lineage, included in the server","The same client interface the ML ecosystem already speaks",[17,18,19,20,21],"ML teams tracking experiments and model versions on their own infrastructure","Training jobs on cloud GPUs that log to one central tracking server","Organizations whose model data and metrics must not leave their network","Small teams replacing ad-hoc spreadsheets of runs with a model registry","LLM and GenAI projects tracing prompts and evaluations alongside classic ML runs",[23,24,25],"The open standard for experiment tracking: no lock-in, no metering","One server process and a database is the whole platform","Artifacts stay on your storage, not a vendor's",[27,28,29],"Built-in auth is basic (users and permissions, no SSO), and HTTPS is yours to add","The UI is spartan next to hosted tracking platforms","Model serving needs its own stack on top",null,{"popularity":32,"learning_curve":35,"flexibility":38,"performance":40,"portability":42},{"score":33,"reasoning":34},4,"MLflow is the most widely used open-source experiment tracker and is supported by nearly every ML framework and platform.",{"score":36,"reasoning":37},3,"Logging runs takes a few lines of client code; running the server adds a database, an artifact store, auth, and TLS, all of it ordinary infrastructure.",{"score":33,"reasoning":39},"Framework-agnostic tracking, a model registry, and GenAI tracing, with any backend database and any S3-compatible artifact store.",{"score":36,"reasoning":41},"The tracking server is light, so one small instance serves a team; artifact storage grows long before compute does.",{"score":43,"reasoning":44},5,"An open standard on plain PostgreSQL and object storage; the same client code logs to a self-hosted server, Databricks, or SageMaker.",{"database":46,"orm":169,"authentication":173,"analytics":177,"coding_agent":181,"llm":185,"language":189,"frontend_framework":193,"cms":197,"hosting":201,"reverse_proxy":370,"self_hosted_paas":454},{"tools":47,"descriptions":161,"aliases":165,"see_all":166},[48,98,133],{"tool_id":49,"name":50,"slug":51,"tooltip_description":52,"logo_url":53,"logo_bg":54,"pricing_model":55,"learning_curve_score":36,"popularity_score":43,"hosting_assignment_type":59,"hosting_provider_restriction":60,"hosting_target_restriction":60,"hosting_compatible_tool_ids":30,"parent_tool_id":30,"category":61,"subcategory":64,"categories":68,"subcategories":71,"flexibility_score":43,"performance_score":33,"portability_score":43,"is_featured":3,"tags":73,"score_reasonings":90,"published_date":96,"last_updated_date":97},40,"PostgreSQL","postgresql","PostgreSQL is a free, open-source object-relational database known for reliability, standards compliance, and extensibility, with rich data types, JSONB, and a large ecosystem of extensions such as PostGIS and pgvector.","https:\u002F\u002Fassets.tekyous.dev\u002Flogos\u002Ftools\u002Fpostgresql.svg","dark",{"slug":56,"display_name":57,"description":58},"open_source","Open Source","Source code is publicly available and free to use, modify, and distribute. 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It offers a proven, high-performance SQL engine with broad ecosystem support across every major language and platform.","https:\u002F\u002Fassets.tekyous.dev\u002Flogos\u002Ftools\u002Fmysql.svg",{"slug":105,"display_name":106,"description":107},"freemium","Freemium","A free tier is available; additional features, usage limits, or managed hosting require a paid plan.",2,{"category_id":33,"name":62,"slug":63},{"subcategory_id":65,"name":66,"slug":67},[112],{"category_id":33,"name":62,"slug":63,"is_primary":3,"display_order":70},[114],{"subcategory_id":65,"name":66,"slug":67,"category_id":33,"is_primary":3,"display_order":70},false,[117,118,122,123],{"tag_id":87,"name":88,"slug":89,"tag_type":81},{"tag_id":119,"name":120,"slug":121,"tag_type":81},13,"Free Tier","free-tier",{"tag_id":83,"name":84,"slug":85,"tag_type":81},{"tag_id":49,"name":124,"slug":125,"tag_type":126},"Web","web","platform",{"performance":128,"learning_curve":129,"flexibility":130,"popularity":131,"portability":132},"InnoDB delivers solid OLTP throughput for standard read-heavy workloads; query optimizer has historically lagged behind PostgreSQL and MariaDB for complex plans, and thread pooling requires the Enterprise edition.","GUI tools (MySQL Workbench, phpMyAdmin) and extensive tutorials make it highly accessible; basic SQL is straightforward but advanced features like stored procedures and replication configuration require more study.","Covers standard OLTP use cases thoroughly; lacks some advanced SQL features PostgreSQL offers (partial indexes, richer JSON, table inheritance); plugin storage engines add flexibility for specific workloads.","The most widely deployed open-source relational database globally — powering the majority of web applications and the default choice in shared hosting and PHP stacks for decades.","Available on every major cloud as a managed service (RDS, Cloud SQL, Azure Database); supported by every major ORM and language driver; minor SQL dialect quirks can require adjustments when migrating.",{"tool_id":134,"name":135,"slug":136,"tooltip_description":137,"logo_url":138,"logo_bg":139,"pricing_model":140,"learning_curve_score":141,"popularity_score":43,"hosting_assignment_type":142,"hosting_provider_restriction":60,"hosting_target_restriction":60,"hosting_compatible_tool_ids":30,"parent_tool_id":30,"category":143,"subcategory":144,"categories":147,"subcategories":149,"flexibility_score":36,"performance_score":33,"portability_score":43,"is_featured":115,"tags":151,"score_reasonings":155,"published_date":96,"last_updated_date":97},124,"SQLite","sqlite","SQLite is a self-contained, serverless SQL database engine that stores the entire database as a single file on disk. 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It also holds the users and permissions of MLflow's basic auth, so a multi-user server wants it behind it. Back it up alongside the artifact store.","A supported backend store alongside PostgreSQL, and the right pick where your platform already runs MySQL. The trade is documentation gravity: MLflow's guides and examples assume PostgreSQL or SQLite, so MySQL is the standardized-estate choice, not the ecosystem's default.","The zero-setup default: one file on the server's disk, fine for a single-user lab. 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VPS plans require Linux and SSH familiarity to get full value, but the guided setup and AI assistant lower the barrier compared to raw VPS providers like Hetzner.","Shared hosting is intentionally constrained — you run within Hostinger's stack and cannot change the server environment. VPS plans give full root access and can run any Linux workload. The range from shared to VPS covers most beginner-to-intermediate deployment needs, but there is no managed Kubernetes, serverless, or edge compute option.","LiteSpeed with NVMe SSD and built-in caching delivers strong performance for shared hosting — independent benchmarks show sub-1-second load times and 99.96%+ uptime on shared plans. KVM VPS performance is competitive for the price. Not at the level of dedicated cloud providers like DigitalOcean or Hetzner for compute-intensive workloads.","Hostinger is one of the top three most-recommended budget hosts globally, with over 3 million customers and a 4.7\u002F5 Trustpilot score. 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