Search Results for "sql data generator"
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302 projects for "sql data generator" with 2 filters applied:
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MyBatis Dynamic SQL
SQL DSL (Domain Specific Language) for Kotlin and Java
This library is a general-purpose SQL generator. Think of it as a typesafe and expressive SQL DSL (domain-specific language), with support for rendering SQL formatted properly for MyBatis3 and Spring's NamedParameterJDBCTemplate. The library also contains extensions for Kotlin that enable an idiomatic Kotlin DSL for SQL. The library will generate full DELETE, INSERT, SELECT, and UPDATE statements. -
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Better Stack JavaScript client
Better Stack JavaScript client
...Get answers fast with a powerful SQL query builder. No need to learn a new querying language or ask your data analyst. -
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PartiQL Lang Kotlin
PartiQL libraries and tools in Kotlin.
This is a Kotlin implementation of the PartiQL specification. PartiQL is based on SQL-92 and has added support for working with schemaless hierarchical data. PartiQL’s extensions to SQL are easy to understand, treat nested data as first-class citizens, and compose seamlessly with each other and SQL. This repository contains an embeddable reference interpreter, test framework, and tests for PartiQL in Kotlin. -
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Nelmio Alice
Expressive fixtures generator
Nelmio Alice is a PHP library designed to generate complex data fixtures for testing and development environments. It uses YAML, XML, or PHP files to define fixture templates, making it easy to create realistic and varied data sets. Alice integrates well with Doctrine ORM, allowing developers to quickly populate databases with test data, making it especially useful for automated testing and staging environments. -
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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Kotlin Dataframe
Structured data processing in Kotlin
Data frame is an abstraction for working with structured data. Essentially it’s a 2-dimensional table with labeled columns of potentially different types. You can think of it like a spreadsheet or SQL table, or a dictionary of series objects. The handiness of this abstraction is not in the table itself but in a set of operations defined on it. -
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dplyr
dplyr: A grammar of data manipulation
dplyr is an R package that provides a consistent and intuitive grammar for data manipulation, enabling users to filter, arrange, summarize, and transform data efficiently. Part of the tidyverse ecosystem, dplyr simplifies complex data operations through a clear and readable syntax, whether working with data frames, tibbles, or databases. It is widely used in data science and statistical analysis workflows. -
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Neosync
Open Source Data Security Platform for Developers to Monitor
Neosync is a secure, open-source platform to generate, mask, and sync realistic test data across environments. It helps engineering teams create privacy-compliant datasets using synthetic data, transformations, and pseudonymization techniques. Designed with extensibility and data governance in mind, Neosync integrates with common databases and cloud services, enabling safe test environments for development and QA. -
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Ktorm
A lightweight ORM framework for Kotlin with strong-typed SQL DSL
Ktorm is a lightweight and efficient ORM Framework for Kotlin directly based on pure JDBC. It provides strong-typed and flexible SQL DSL and convenient sequence APIs to reduce our duplicated effort on database operations. All the SQL statements, of course, are generated automatically. Ktorm is open source and available under the Apache 2.0 license. Please leave a star if you've found this library helpful. -
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Apache Sedona
Cluster computing framework for processing large-scale geospatial data
Apache Sedona™ is a cluster computing system for processing large-scale spatial data. Sedona extends existing cluster computing systems, such as Apache Spark and Apache Flink, with a set of out-of-the-box distributed Spatial Datasets and Spatial SQL that efficiently load, process, and analyze large-scale spatial data across machines. According to our benchmark and third-party research papers, Sedona runs 2X - 10X faster than other Spark-based geospatial data systems on computation-intensive query workloads. ... -
Gemini 3 and 200+ AI Models on One PlatformBuild generative AI apps with Vertex AI. Switch between models without switching platforms.
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Seal Report
Database Reporting Tool and Tasks (.Net)
Seal Report is an open-source tool for the generation of daily reports from any database. It offers a complete framework for producing dynamic reports and dashboards, with a focus on simplicity and ease of use. -
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Smallpond
A lightweight data processing framework built on DuckDB and 3FS
...Users write Python-like code (via DataFrame APIs or SQL strings) to express their transformations; behind the scenes, tasks are scheduled (often via Ray) and pushed into DuckDB instances operating on partitioned data. Because the storage layer (3FS) is optimized for random access and high throughput, smallpond can shuffle data, repartition, and manage intermediate results across nodes. -
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JsStore
A complete IndexedDB wrapper with SQL like syntax
Execute Database operation in browsers with JsStore. JsStore is an indexedDB wrapper. It makes IndexedDB super easy with its SQL-like APIs. Harness the power of JsStore to streamline database operations in your web applications. With its SQL-like API, JsStore simplifies IndexedDB interactions, enabling developers to easily query, filter, and manipulate data with familiar syntax and efficiency. -
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Apache Spark
A unified analytics engine for large-scale data processing
Apache Spark is a unified engine for large-scale data processing, offering APIs for batch jobs, streaming, machine learning, and graph computation. It builds on resilient distributed datasets (RDDs) and the newer DataFrame/Dataset abstractions to provide fault-tolerant, in-memory computation across clusters. Spark’s execution engine handles scheduling, shuffles, caching, and data locality so users can focus on transformations rather than infrastructure plumbing. With Spark Streaming... -
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Siddhi Core Libraries
Stream Processing and Complex Event Processing Engine
Fully open source, cloud-native, scalable, micro streaming, and complex event processing system capable of building event-driven applications for use cases such as real-time analytics, data integration, notification management, and adaptive decision-making. Event processing logic can be written using Streaming SQL queries via graphical and source editors, to capture events from diverse data sources, process and analyze them, integrate with multiple services and data stores, and publish output to various endpoints in real time. ... -
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Polars
Dataframes powered by a multithreaded, vectorized query engine
Polars is a high-performance, multi-language DataFrame library built in Rust using Apache Arrow. 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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Steampipe
Zero-ETL, infinite possibilities. Live query APIs, code & more
Steampipe is the zero-ETL solution for getting data directly from APIs and services. We offer these Steampipe engines. SQL has been the data access standard for decades. It levels the playing field for your team, easily integrates with other systems, and accelerates delivery. Painlessly join live cloud configuration data with internal or external data sets to create new insights. Your cloud is a live database that changes fast. -
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GoogleSQL
GoogleSQL (formerly ZetaSQL) - Analyzer Framework for SQL
GoogleSQL is a reusable SQL language framework designed to standardize how SQL is written and analyzed across different systems. Previously called ZetaSQL, it defines core elements such as syntax, data models, type systems, and query semantics. Rather than executing queries, GoogleSQL focuses on parsing and validating SQL statements. It ensures consistent behavior for tasks like name resolution, type validation, and automatic casting. -
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Apache Drill
Apache Drill is a distributed MPP query layer for self describing data
Apache Drill is a distributed MPP query layer that supports SQL and alternative query languages against NoSQL and Hadoop data storage systems. It was inspired in part by Google's Dremel. Get faster insights without the overhead (data loading, schema creation and maintenance, transformations, etc.) Analyze the multi-structured and nested data in non-relational datastores directly without transforming or restricting the data. -
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Jigsaw
Simple static sites with Laravel’s Blade
Jigsaw is a static site generator for PHP developers, created by Tighten. It provides a Laravel-inspired development environment for building static websites and documentation sites using Blade templates and Markdown content. Jigsaw is particularly suited for developers familiar with Laravel who want to create simple, fast, and maintainable sites. -
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EFCore.BulkExtensions
Entity Framework EF Core efcore Bulk Batch Extensions with BulkCopy
EFCore.BulkExtensions is a high-performance extension library for Entity Framework Core that provides bulk operations like insert, update, delete, and read. It significantly improves performance when working with large datasets and supports batching, upserts, and change tracking. The library is compatible with popular databases like SQL Server, PostgreSQL, MySQL, and SQLite. -
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SonataAdminBundle
The missing Symfony Admin Generator
SonataAdminBundle is a powerful Symfony bundle that enables developers to create customizable admin panels for managing data in web applications. It provides a ready-to-use interface that can handle complex forms, CRUD operations, and entity relationships. Designed with extensibility in mind, SonataAdminBundle supports integration with other Symfony bundles and offers a solid foundation for building scalable back-office systems. -
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Fast Paginate for Laravel
A fast implementation of offset/limit pagination for Laravel.
This is a fast limit/offset pagination macro for Laravel. It can be used in place of the standard paginate methods. This package uses a SQL method similar to a "deferred join" to achieve this speedup. A deferred join is a technique that defers access to requested columns until after the offset and limit have been applied. In our case we don't actually do a join, but rather a where in with a subquery. Using this technique we create a subquery that can be optimized with specific indexes for... -
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tableExport.jquery.plugin
jQuery plugin to export a html table to JSON, XML, CSV, TSV, TXT, SQL
jQuery plugin to export an html table to JSON, XML, CSV, TSV, TXT, SQL, Word, Excel, PNG, and PDF. -
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jimmer
A revolutionary ORM framework for both java and kotlin.
...You can view everything from the documentation. Brings dynamism into static language ORM frameworks, achieving flexible capabilities for operating on complex dynamic data structures without compromising the complete compile-time safety checks of static languages, eliminating DTO explosion and unafraid of engineering expansion and changing requirements. Its innovative SQL DSL supports dynamic table joins and native SQL embedding, gracefully handling real-world complexity. Focuses on business and reaping caching gains. ... -
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Perfetto
Production-grade client-side tracing, profiling, and analysis
...It’s designed around a low-overhead producer/consumer model: instrumented components (“producers”) write binary events into shared memory buffers and a collector (“service”) reliably streams them to storage. The data model spans kernel and userspace, so you can stitch together CPU scheduling, app lifecycles, binder/IPC hops, GPU work, power and thermal signals, file I/O, heap samples, and more into a single coherent timeline. Perfetto’s ecosystem includes a web-based UI that can load multi-GB traces directly in the browser and an offline “trace processor” that exposes the trace as a queryable SQL-like table schema for deep analysis and automation. ...
