SQLAlchemy Integrations

DataHub Cloud is an event-driven AI & Data Context Platform that uses active metadata for real-time visibility across your entire data ecosystem. Unlike traditional data catalogs that provide outdated snapshots, DataHub Cloud instantly propagates changes, automatically enforces policies, and connects every data source across platforms with 100+ pre-built connectors. Built on an open source foundation with a thriving community of 13,000+ members, DataHub gives you unmatched flexibility to customize and extend without vendor lock-in. DataHub Cloud is a modern metadata platform with REST and GraphQL APIs that optimize performance for complex queries, essential for AI-ready data management and ML lifecycle support.

SQLite is a C-language library that implements a small, fast, self-contained, high-reliability, full-featured, SQL database engine. SQLite is the most used database engine in the world. SQLite is built into all mobile phones and most computers and comes bundled inside countless other applications that people use every day. SQLite is an in-process library that implements a self-contained, serverless, zero-configuration, transactional SQL database engine. The code for SQLite is in the public domain and is thus free for use for any purpose, commercial or private. SQLite is the most widely deployed database in the world with more applications than we can count, including several high-profile projects.

MySQL is the world's most popular open source database. With its proven performance, reliability, and ease-of-use, MySQL has become the leading database choice for web-based applications, used by high profile web properties including Facebook, Twitter, YouTube, and all five of the top five websites*. Additionally, it is an extremely popular choice as embedded database, distributed by thousands of ISVs and OEMs.

Intelligence and security are built into Microsoft SQL Server 2019. You get extras without extra cost, along with best-in-class performance and flexibility for your on-premises needs. Take advantage of the efficiency and agility of the cloud by easily migrating to the cloud without changing code. Unlock insights and make predictions faster with Azure. Develop using the technology of your choice, including open source, backed by Microsoft's innovations. Easily integrate data into your apps and use a rich set of cognitive services to build human-like intelligence across any scale of data. AI is native to the data platform—you can unlock insights faster from all your data, on-premises and in the cloud. Combine your unique enterprise data and the world's data to build an intelligence-driven organization. Work with a flexible data platform that gives you a consistent experience across platforms and gets your innovations to market faster—you can build your apps and then deploy anywhere.

Over 1,500 development teams trust AppSignal to ship code with confidence. AppSignal’s all-in-one monitoring toolkit gives developers the insights they need to monitor and maintain their apps with ease. AppSignal's toolkit includes performance monitoring, error tracking, log and host management, uptime checks, and more in one intuitive interface. Unlike more complex tools, AppSignal is built for simplicity with fast setup, helpful support, and transparent pricing that’s affordable for any team at any scale. AppSignal provides the bloat-free tooling developers need to focus on deploying instead of debugging.

Union.ai is an award-winning, Flyte-based data and ML orchestrator for scalable, reproducible ML pipelines. With Union.ai, you can write your code locally and easily deploy pipelines to remote Kubernetes clusters. “Flyte’s scalability, data lineage, and caching capabilities enable us to train hundreds of models on petabytes of geospatial data, giving us an edge in our business.” — Arno, CTO at Blackshark.ai “With Flyte, we want to give the power back to biologists. We want to stand up something that they can play around with different parameters for their models because not every … parameter is fixed. We want to make sure we are giving them the power to run the analyses.” — Krishna Yeramsetty, Principal Data Scientist at Infinome “Flyte plays a vital role as a key component of Gojek's ML Platform by providing exactly that." — Pradithya Aria Pura, Principal Engineer at Goj

The workflow automation platform for complex, mission-critical data and ML processes at scale. Flyte makes it easy to create concurrent, scalable, and maintainable workflows for machine learning and data processing. Flyte is used in production at Lyft, Spotify, Freenome, and others. At Lyft, Flyte has been serving production model training and data processing for over four years, becoming the de-facto platform for teams like pricing, locations, ETA, mapping, autonomous, and more. In fact, Flyte manages over 10,000 unique workflows at Lyft, totaling over 1,000,000 executions every month, 20 million tasks, and 40 million containers. Flyte has been battle-tested at Lyft, Spotify, Freenome, and others. It is entirely open-source with an Apache 2.0 license under the Linux Foundation with a cross-industry overseeing committee. Configuring machine learning and data workflows can get complex and error-prone with YAML.

Hue brings the best querying experience with the most intelligent autocomplete and query editor components. The tables and storage browsers leverage your existing data catalog knowledge transparently. Help users find the correct data among thousands of databases and self-document it. Assist users with their SQL queries and leverage rich previews for links, sharing from the editor directly in Slack. Several apps, each one specialized in a certain type of querying are available. Data sources can be explored first via the browsers. The editor shines for SQL queries. It comes with an intelligent autocomplete, risk alerts, and self-service troubleshooting. Dashboards focus on visualizing indexed data but can also query SQL databases. You can now search for certain cell values in the table and the results are highlighted. To make your SQL editing experience, Hue comes with one of the best SQL autocomplete on the planet.

Alembic is a lightweight database migration tool that can be used with the SQLAlchemy database toolkit for Python. Alembic is written by the author of SQLAlchemy. While Alembic can be installed system-wide, it’s more common that it’s installed locally in a virtual environment, as it also uses libraries such as SQLAlchemy and database drivers that are more appropriate for local installations. Can emit statements to a database in order to change the structure of tables and other constructs. Provides a system whereby "migration scripts" may be constructed; each script indicates a particular series of steps that can "upgrade" a target database to a new version, and optionally a series of steps that can "downgrade" similarly, doing the same steps in reverse. Very open-ended and transparent configuration and operation. A new Alembic environment is generated from a set of templates which is selected among a set of options when setup first occurs.

Timbr is the ontology-based semantic layer used by leading enterprises to make faster, better decisions with ontologies that transform structured data into AI-ready knowledge. By unifying enterprise data into a SQL-queryable knowledge graph, Timbr makes relationships, metrics, and context explicit, enabling both humans and AI to reason over data with accuracy and speed. Its open, modular architecture connects directly to existing data sources, virtualizing and governing them without replication. The result is a dynamic, easily accessible model that powers analytics, automation, and LLMs through SQL, APIs, SDKs, and natural language. Timbr lets organizations operationalize AI on their data - securely, transparently, and without dependence on proprietary stacks - maximizing data ROI and enabling teams to focus on solving problems instead of managing complexity.

Pydantic Logfire is an observability platform designed to simplify monitoring for Python applications by transforming logs into actionable insights. It provides performance insights, tracing, and visibility into application behavior, including request headers, body, and the full trace of execution. Pydantic Logfire integrates with popular libraries and is built on top of OpenTelemetry, making it easier to use while retaining the flexibility of OpenTelemetry's features. Developers can instrument their apps with structured data, and query-ready Python objects, and gain real-time insights through visualizations, dashboards, and alerts. Logfire also supports manual tracing, context logging, and exception capturing, providing a modern logging interface. It is tailored for developers seeking a streamlined, effective observability tool with out-of-the-box integrations and ease of use.

Firebird is a relational database offering many ANSI SQL standard features that runs on Linux, Windows, and a variety of Unix platforms. Firebird offers excellent concurrency, high performance, and powerful language support for stored procedures and triggers. It has been used in production systems, under a variety of names, since 1981. The Firebird Project is a commercially independent project of C and C++ programmers, technical advisors and supporters developing and enhancing a multi-platform relational database management system based on the source code released by Inprise Corp (now known as Borland Software Corp) on 25 July, 2000. The Firebird Project supplies users, developers, and administrators with various kinds of documentation, from Quick Start guides to expert-level articles devoted to various aspects of Firebird.

OpenMetadata is an open, unified metadata platform that centralizes all metadata for data discovery, observability, and governance in a single interface. It leverages a Unified Metadata Graph and 80+ turnkey connectors to collect metadata from databases, pipelines, BI tools, ML systems, and more, providing a complete data context that enables teams to search, facet, and preview assets across their entire estate. Its API‑ and schema‑first architecture offers extensible metadata entities and relationships, giving organizations precise control and customization over their metadata model. Built with only four core system components, the platform is designed for simple setup, operation, and scalable performance, allowing both technical and non‑technical users to collaborate on discovery, lineage, quality, observability, collaboration, and governance workflows without complex infrastructure.

Oracle Cloud Infrastructure supports traditional workloads and delivers modern cloud development tools. It is architected to detect and defend against modern threats, so you can innovate more. Combine low cost with high performance to lower your TCO. Oracle Cloud is a Generation 2 enterprise cloud that delivers powerful compute and networking performance and includes a comprehensive portfolio of infrastructure and platform cloud services. Built from the ground up to meet the needs of mission-critical applications, Oracle Cloud supports all legacy workloads while delivering modern cloud development tools, enabling enterprises to bring their past forward as they build their future. Our Generation 2 Cloud is the only one built to run Oracle Autonomous Database, the industry's first and only self-driving database. Oracle Cloud offers a comprehensive cloud computing portfolio, from application development and business analytics to data management, integration, security, AI & blockchain.

PostgreSQL is a powerful, open-source object-relational database system with over 30 years of active development that has earned it a strong reputation for reliability, feature robustness, and performance. There is a wealth of information to be found describing how to install and use PostgreSQL through the official documentation. The open-source community provides many helpful places to become familiar with PostgreSQL, discover how it works, and find career opportunities. Learm more on how to engage with the community. The PostgreSQL Global Development Group has released an update to all supported versions of PostgreSQL, including 15.1, 14.6, 13.9, 12.13, 11.18, and 10.23. This release fixes 25 bugs reported over the last several months. This is the final release of PostgreSQL 10. PostgreSQL 10 will no longer receive security and bug fixes. If you are running PostgreSQL 10 in a production environment, we suggest that you make plans to upgrade.

No more data catalog ghost towns. Acryl Cloud drives fast time-to-value via Shift Left practices for data producers and an intuitive UI for data consumers. Continuously detect data quality incidents in real-time, automate anomaly detection to prevent breakages, and drive fast resolution when they do occur. Acryl Cloud supports both push-based and pull-based metadata ingestion for easy maintenance, ensuring information is trustworthy, up-to-date, and definitive. Data should be operational. Go beyond simple visibility and use automated Metadata Tests to continuously expose data insights and surface new areas for improvement. Reduce confusion and accelerate resolution with clear asset ownership, automatic detection, streamlined alerts, and time-based lineage for tracing root causes.