Search Results for "ms-sql"
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Showing 12 open source projects for "ms-sql"
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pg_graphql
GraphQL support for PostgreSQL
pg_graphql is a PostgreSQL extension that enables querying the database with GraphQL using a single a SQL function. The extension reflects a GraphQL schema from the existing SQL schema and exposes it through a SQL function, graphql. resolve(...). This enables any programming language that can connect to PostgreSQL to query the database via GraphQL with no additional servers, processes, or libraries. Each table receives an entry point in the top-level Query type that is a pageable collection with relationships defined by its foreign keys. ... -
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Polars
Dataframes powered by a multithreaded, vectorized query engine
...It delivers blazing-fast, vectorized, and parallel data manipulation with both eager and lazy execution, making it an excellent tool for data processing in Python, Rust, Node.js, R, and SQL contexts. -
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Rbatis
Rust High Performance compile-time ORM(RBSON based)
A highly Performant, Safe, Dynamic SQL(Compile-time) ORM framework written in Rust, inspired by Mybatis and MybatisPlus. Zero cost Dynamic SQL, implemented using (proc-macro,compile-time, Cow (Reduce unnecessary cloning)) techniques, don't need ONGL engine(mybatis) Free deserialization, Auto Deserialize to any struct(Option,Map,Vec...) High performance, Based on Future, with async_std/tokio, single threaded benchmark can easily achieve 200,000 QPS. logical deletes, pagination, py-like SQL and basic Mybatis functionalities. ... -
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PgRx
Build Postgres Extensions with Rust
pgrx is a Rust framework for developing PostgreSQL extensions, making it easier to write safe, high-performance native extensions in Rust. It handles the boilerplate and unsafe FFI needed to interface with Postgres internals, allowing developers to focus on logic. With built-in support for SQL generation, testing, and deployment, pgrx streamlines the extension creation process while embracing Rust’s safety guarantees. -
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5
Diesel
A safe, extensible ORM and Query Builder for Rust
...We achieve this by having Diesel eliminate the possibility of incorrect database interactions at compile time. Diesel offers a high level query builder and lets you think about your problems in Rust, not SQL. Our focus on zero-cost abstractions allows Diesel to run your query and load your data even faster than C. Unlike Active Record and other ORMs, Diesel is designed to be abstracted over. Diesel enables you to write reusable code and think in terms of your problem domain and not SQL. -
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ROAPI
Create full-fledged APIs for slowly moving datasets without writing
...ROAPI automatically spins up read-only APIs and query frontends for slowly moving datasets without requiring you to write a single line of code. It builds on top of Apache Arrow and Datafusion. Query frontends to translate SQL, GraphQL and REST API queries into Datafusion plans. Datafusion for query plan execution. Data layer to load datasets from a variety of sources and formats with automatic schema inference. Response encoding layer to serialize intermediate Arrow record batch into various formats requested by the client. Its pluggable query core design makes it possible for users to efficiently perform join queries across a diverse set of data sources from simple CSV/Parquet files in Data warehouses to MySQL/Postgres, to SASS-like Google spreadsheets. -
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Nushell
A new type of shell
NuShell (often shortened to “Nu”) is a modern, cross-platform shell written in Rust that treats all data as structured tables rather than plain text. It supports pipelines on rich typed data, has built-in commands for JSON/CSV/SQL/excel, and offers scripting, autocompletion, scoped variables, and strong error handling—bridging the gap between shell scripting and programming. -
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Mangle
Go library for Datalog-style logical reasoning and domain modeling
...Mangle enhances traditional Datalog by introducing features such as aggregation, function calls, and optional type-checking, which make it more practical for modern data-intensive applications. Unlike SQL, Mangle’s declarative syntax naturally supports recursion and modular program structure, making it suitable for representing hierarchical or interconnected datasets like dependency graphs or knowledge graphs. The project’s implementation is provided as a Go library, enabling developers to embed Mangle directly into their applications or services, such as database-like gRPC systems. -
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GritQL
GritQL is a query language for searching, linting, and modifying code
GritQL is a query language designed to facilitate human-AI collaboration by providing an intuitive interface for querying and retrieving structured data. It acts as a bridge between AI models and databases, enabling natural language interaction with structured data sources. -
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10
agentOS
A portable open-source operating system for agents. ~6 ms coldstarts
agentOS is a portable, open-source runtime environment designed specifically for executing AI agents efficiently, acting as a lightweight operating system tailored for agent-based workloads. It is built using WebAssembly and V8 isolates to provide secure, sandboxed execution without the overhead of traditional containers or virtual machines. The system is optimized for extremely fast startup times, with near-instant cold starts that allow agents to be created and executed in milliseconds.... -
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SafeUtils
110+ developer tools as native MacOS, Linux & Windows desktop apps.
Tools: https://safeutils.com/barcode-generator https://safeutils.com/color-picker https://safeutils.com/qr-code-generator https://safeutils.com/qr-code-scanner https://safeutils.com/word-counter https://safeutils.com/base-64-decoder https://safeutils.com/diff-checker https://safeutils.com/hex-to-ascii https://safeutils.com/json-formatter https://safeutils.com/lorem-ipsum-generator https://safeutils.com/random-generator https://safeutils.com/time-converter https://safeutils.com/... -
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Synth
The Declarative Data Generator
...Synth can import data straight from existing sources and automatically create accurate and versatile data models. Synth supports semi-structured data and is database agnostic, playing nicely with SQL and NoSQL databases. Synth supports generation for thousands of semantic types such as credit card numbers, email addresses, and more.
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