Search Results for "sql data generator"
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Showing 32 open source projects for "sql data generator"
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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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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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SQLpage
Fast SQL-only data application builder
SQLPage is a rapid application development tool that enables developers to build data-driven web applications using only SQL queries. By writing simple .sql files, users can create interactive web pages that display data as text, lists, grids, plots, and forms, streamlining the process of developing data applications without extensive frontend coding. -
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RisingWave
RisingWave: the next-generation streaming database in the cloud
...Everything you do in RisingWave is via Postgres-compatible SQL. Create materialized views for the data that need to be incrementally aggregated. Query for data in RisingWave, including persisted data and data you add or import to RisingWave. RisingWave makes it easy to manage streams and data. All you need to interact with RisingWave is Postgres-compatible SQL. No Java or Scala codes are needed. -
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Turso Database
Turso is an in-process SQL database, compatible with SQLite
Turso is an in-process SQL database written in Rust and designed to stay compatible with SQLite. It supports SQLite’s SQL dialect, file formats, and C API while adding newer database capabilities. The project is currently in beta, so it is best used with care and proper backups for production data. Turso includes support for concurrent writes through MVCC, change data capture, and faster schema management. -
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Cube
Universal semantic layer platform for AI, BI, spreadsheets
Cube is the semantic layer for building data applications. It helps data engineers and application developers access data from modern data stores, organize it into consistent definitions, and deliver it to every application. Cube was designed to work with all SQL-enabled data sources, including cloud data warehouses like Snowflake or Google BigQuery, query engines like Presto or Amazon Athena, and application databases like Postgres. ... -
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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Lantern Database
PostgreSQL vector database extension for building AI applications
Lantern is a real-time data transformation engine that enables data engineers to build, run, and monitor streaming data pipelines with SQL. It’s designed to process events in motion, offering low-latency stream transformations, aggregations, and enrichment in a declarative way. Lantern is especially suited for modern data infrastructure and analytics platforms. -
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Supabase Wrappers
Postgres Foreign Data Wrapper development framework in Rust
Supabase Wrappers is a collection of PostgreSQL extensions (written in Rust) that allow Postgres to interact with external systems like APIs, files, and other databases. It uses Foreign Data Wrappers (FDWs) to treat external resources as if they were native SQL tables, enabling seamless integration with external services directly from SQL queries. -
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Coral
One SQL interface over APIs, files, and live sources
Coral is a local-first SQL runtime that lets agents query APIs, files, and live data sources through a single interface. It is designed to make external data easier for AI agents to inspect, structure, and use without requiring a different integration pattern for every service. The project gives developers a command-line workflow for querying data, inspecting schemas, and working with tables. -
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Databend
Cloud-native open source data warehouse for analytics and AI queries
...This architecture enables cost-efficient storage and elastic scaling for workloads that involve large datasets and complex queries. Databend provides a unified engine capable of handling analytics, vector search, and full-text search within a single platform. Databend supports SQL-based workflows and enables real-time data ingestion, transformation, and analysis through streaming and task orchestration features. With its cloud-native design and distributed architecture, Databend can run both as a self-hosted system or within managed environments to power data analytics, AI workloads, and large-scale data. -
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QSV
Blazing-fast Data-Wrangling toolkit
qsv is a fast, command-line CSV data toolkit written in Rust that extends the capabilities of xsv. It’s designed to make working with CSV files at scale easy and efficient, offering over 40 powerful subcommands for tasks like querying, sampling, splitting, deduplicating, and more. qsv is ideal for data engineers, analysts, and developers who need high-performance CSV manipulation on the command line. -
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Arroyo
Distributed stream processing engine in Rust
Arroyo is a distributed stream processing engine written in Rust, designed to efficiently perform stateful computations on streams of data. Unlike traditional batch processing, streaming engines can operate on both bounded and unbounded sources, emitting results as soon as they are available. -
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Spice.ai OSS
A self-hostable CDN for databases
Spice is a portable runtime offering developers a unified SQL interface to materialize, accelerate, and query data from any database, data warehouse, or data lake. Spice connects, fuses, and delivers data to applications, machine-learning models, and AI backends, functioning as an application-specific, tier-optimized Database CDN. The Spice runtime, written in Rust, is built-with industry-leading technologies such as Apache DataFusion, Apache Arrow, Apache Arrow Flight, SQLite, and DuckDB. ... -
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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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GreptimeDB
An open-source, cloud-native, unified time series database for metrics
GreptimeDB treats all time series as contextual events with timestamps, and thus unifies the processing of metrics, logs, and events. It supports analyzing metrics, logs, and events with SQL, PromQL, and streaming with continuous aggregation. GreptimeDB is a time-series database optimized for storing and querying large amounts of time-series data, commonly used in monitoring and IoT applications. -
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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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OpenObserve
Elasticsearch/Splunk/Datadog alternative for (logs, metrics, traces)
OpenObserve is a cloud-native observability platform built specifically for logs, metrics, traces, and analytics designed to work at a petabyte scale. It is very simple and easy to operate as opposed to Elasticsearch which requires a couple of dozen knobs to understand and tune which you can get up and running in under 2 minutes. It is a drop-in replacement for Elasticsearch if you are just ingesting data using APIs and searching using Kibana (Kibana is not supported nor required with... -
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SurrealDB
A scalable, distributed, collaborative, document-graph database
With an SQL-style query language, real-time queries with highly-efficient related data retrieval, advanced security permissions for multi-tenant access, and support for performant analytical workloads, SurrealDB is the next generation serverless database. SurrealDB is the ultimate cloud database for tomorrow's applications. SurrealDB is an innovative NewSQL cloud database, suitable for serverless applications, jamstack applications, single-page applications, and traditional applications. ... -
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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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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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parseable
Parseable is a log analytics system written in Rust
Parseable is a log analytics platform, built for the modern, cloud native era. Parseable uses a index-free mechanism to organize and query data allowing low latency, and high throughput ingestion and query. -
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PostgresML
The GPU-powered AI application database
...Leverage multiple types of natural language processing and machine learning models such as vector search and personalization with embeddings to improve search results. Leverage your data with time series forecasting to garner key business insights. Build statistical and predictive models with the full power of SQL and dozens of regression algorithms. Return results and detect fraud faster with ML at the database layer. PostgresML abstracts the data management overhead from the ML/AI lifecycle by enabling users to run ML/LLM models directly on a Postgres database. -
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Stoolap
A Modern Embedded SQL Database written in Rust
Stoolap is a lightweight, self-hosted analysis and visualization tool designed to help developers and operations teams explore log data, metrics, and debugging information from distributed systems or local applications. Instead of relying on heavy commercial observability platforms, stoolap provides a fast, focused interface where users can filter, query, and visualize time-series data, logs, traces, and error metrics in a cohesive environment. Its intuitive query builder lets users craft... -
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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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Mangle
Go library for Datalog-style logical reasoning and domain modeling
Mangle is a programming language developed by Google for deductive database programming, serving as an advanced extension of Datalog. It is designed to unify and query data from multiple sources in a structured, declarative way while allowing developers to model complex relationships and domain knowledge beyond binary predicates. 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. ... -
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Sail
A drop-in Apache Spark replacement written in Rust
...It is built entirely in Rust, eliminating JVM overhead and enabling predictable performance, fast startup times, and improved memory safety compared to traditional big data frameworks. Sail is compatible with the Spark Connect protocol, which means existing Spark SQL and DataFrame workloads can run without code changes, making adoption seamless for teams already using Spark-based pipelines. The framework is designed to operate across a variety of environments, including local machines, Kubernetes clusters, and cloud deployments, allowing flexible scaling based on workload requirements. ... -
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Korvus
Korvus is a search SDK that unifies the entire RAG pipeline
Korvus is an open-source retrieval-augmented generation (RAG) pipeline designed to run entirely inside PostgreSQL, allowing developers to build AI search and knowledge systems directly within a database environment. The project consolidates the typical steps of a RAG pipeline—including embedding generation, document retrieval, reranking, and text generation—into a single query executed within the Postgres ecosystem. By leveraging PostgresML and vector extensions such as pgvector, Korvus...
