Search Results for "pl/sql"
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Showing 147 open source projects for "pl/sql"
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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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8 Monitoring Tools in One APM. Install in 5 Minutes.AppSignal works out of the box for Ruby, Elixir, Node.js, Python, and more. 30-day free trial, no credit card required.
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Azure Data Studio
A data management tool that enables working with other SQL tools
...Use Azure Data Studio to query, design, and manage your databases and data warehouses wherever they are, on your local computer or in the cloud. Azure Data Studio offers a modern, keyboard-focused SQL coding experience that makes your everyday tasks easier with built-in features, such as multiple tab windows, a rich SQL editor, IntelliSense, keyword completion, code snippets, code navigation, and source control integration (Git). -
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SQLPad
Web-based SQL editor run in your own private cloud
A web app for writing and running SQL queries and visualizing the results. Supports Postgres, MySQL, SQL Server, ClickHouse, Crate, Vertica, Trino, Presto, SAP HANA, Cassandra, Snowflake, Google BigQuery, SQLite, TiDB, and many more via ODBC. The docker image runs on port 3000 and uses /var/lib/sqlpad for the embedded database directory. latest tag is continuously built from latest commit in repo. -
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Bdash
Simple SQL Client for lightweight data analysis
Simple SQL Client for lightweight data analysis. You can share the result with gist. Supports MySQL, PostgreSQL (Amazon Redshift), SQLite3, Google BigQuery, Treasure Data, Amazon Athena. You can download and install from Web Site or Releases. -
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FunSQL.jl
Julia library for compositional construction of SQL queries
FunSQL is a Julia library for the compositional construction of SQL queries. Julia programmers sometimes need to interrogate data with the Structured Query Language (SQL). But SQL is notoriously hard to write in a modular fashion. FunSQL exposes full expressive power of SQL with compositional semantics. FunSQL allows you to build queries incrementally from small independent fragments. This approach is particularly useful for building applications that programmatically construct SQL queries. -
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Metabase
The simplest, fastest way to share business intelligence and analytics
Metabase is the easiest way to let everyone in your company access business data and analytics, learn from it and ask questions. Even if you or your colleagues have no experience in SQL, you can easily summarize and visualize your data, share it and let your team ask questions about it. Metabase creates beautiful graphs and charts, with an easy-to-use dashboard where everyone can create, organize and share exceptionally visualized data. It supports a great number of databases, including Postgres, MySQL, Druid, MongoDB, SQLite and more. ... -
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DuckDB
DuckDB is an in-process SQL OLAP Database Management System
DuckDB is a high-performance analytical database system. It is designed to be fast, reliable and easy to use. DuckDB provides a rich SQL dialect, with support far beyond basic SQL. DuckDB supports arbitrary and nested correlated subqueries, window functions, collations, complex types (arrays, structs), and more. For more information on the goals of DuckDB, please refer to the Why DuckDB page on our website. Processing and storing tabular datasets, e.g. from CSV or Parquet files. ... -
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CloudQuery
The open-source cloud asset inventory powered by SQL
CloudQuery extracts, transforms and loads your cloud assets into normalized PostgreSQL tables. CloudQuery enables you to assess, audit, and monitor the configurations of your cloud assets. Use standard SQL to find any asset based on any configuration or relation to other assets. Connect CloudQuery standard PostgreSQL database to your favorite BI/Visualization tool such as Grafana, QuickSight, etc. Codify your security & compliance rules with SQL as the query engine. Integrate CloudQuery with your current visualization, monitoring, and alerting such as Grafana. ... -
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Mage.ai
Build, run, and manage data pipelines for integrating data
...No more DAGs with spaghetti code. Start developing locally with a single command or launch a dev environment in your cloud using Terraform. Write code in Python, SQL, or R in the same data pipeline for ultimate flexibility. -
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Superset
Apache Superset is a data visualization and data exploration platform
...Superset is fast, lightweight, intuitive, and loaded with options that make it easy for users of all skill sets to explore and visualize their data, from simple line charts to highly detailed geospatial charts. Quickly and easily integrate and explore your data, using either our simple no-code viz builder or state-of-the-art SQL IDE. Superset can connect to any SQL-based data source through SQLAlchemy, including modern cloud-native databases and engines at a petabyte-scale. Superset is lightweight and highly scalable, leveraging the power of your existing data infrastructure without requiring yet another ingestion layer. Superset ships with a wide array of beautiful visualizations. ... -
Fully Managed MySQL, PostgreSQL, and SQL ServerCloud SQL handles your database ops end to end, so you can focus on your app.
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Cube
Universal semantic layer platform for AI, BI, spreadsheets
...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. Cube has a built-in relational caching engine to provide sub-second latency and high concurrency for API requests. -
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Quadratic
Data science spreadsheet with Python & SQL
...Our goal is to build a spreadsheet that enables you to pull your data from its source (SaaS, Database, CSV, API, etc) and then work with that data using the most popular data science tools today (Python, Pandas, SQL, JS, Excel Formulas, etc). Quadratic has no environment to configure. The grid runs entirely in the browser with no backend service. This makes our grids completely portable and very easy to share. Quadratic has Python library support built-in. Bring the latest open-source tools directly to your spreadsheet. Quickly write code and see the output in full detail. ... -
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DQO Data Quality Operations Center
Data Quality Operations Center
...DQO comes with around 100 predefined data quality checks which helps you monitor the quality of your data. Table and column-level checks which allows writing your own SQL queries. Daily and monthly date partition testing. Data segmentation by up to 9 different data streams. Build-in scheduling. Calculation of data quality KPIs which can be displayed on multiple built-in data quality dashboards. -
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AI Data Science Team
An AI-powered data science team of agents
...It provides a modular agent framework where each agent focuses on a step in the typical data science pipeline — for example, loading data from CSV/Excel files, cleaning and wrangling messy datasets, engineering predictive features, building models with AutoML, connecting to SQL databases, and producing visual outputs — all driven by natural language or programmatic instructions. The project includes ready-to-use applications that showcase these agents in action, such as an exploratory data analysis copilot that generates reports, a pandas data analyst that combines wrangling and plotting, and SQL database agents that can query business databases and output results directly. -
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Apache Doris
MPP-based interactive SQL data warehousing for reporting and analysis
...Apache Doris can meet various data analysis demands, including history data reports, real-time data analysis, interactive data analysis, and exploratory data analysis. Make your data analysis easier! Support standard SQL language, compatible with MySQL protocol. The main advantages of Doris are the simplicity (of developing, deploying and using) and meeting many data serving requirements in a single system. Doris mainly integrates the technology of Google Mesa and Apache Impala, and it is based on a column-oriented storage engine and can communicate by MySQL client. -
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sparklyr
R interface for Apache Spark
sparklyr is an R package that provides seamless interfacing with Apache Spark clusters—either local or remote—while letting users write code in familiar R paradigms. It supplies a dplyr-compatible backend, Spark machine learning pipelines, SQL integration, and I/O utilities to manipulate and analyze large datasets distributed across cluster environments. -
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CSV Lint
CSV Lint plug-in for Notepad++ for syntax highlighting
CSV Lint plug-in for Notepad++ for syntax highlighting, csv validation, automatic column and datatype detecting fixed width datasets, change datetime format, decimal separator, sort data, count unique values, convert to xml, json, sql etc. A plugin for data cleaning and working with messy data files. Use CSV Lint for metadata discovery, technical data validation, and reformatting on tabular data files. It is not meant to be a replacement for spreadsheet programs like Excel or SPSS, but rather it's a quality control tool to examine, verify or polish up a dataset before further processing. -
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OrientDB
DBMS supporting graph, document, full-text and geospatial models
...You can traverse thousands of records in no time. Supports schema-less, schema-full and schema-mixed modes. Has a strong security profiling system based on user, roles and predicate security and supports SQL amongst the query languages. Thanks to the SQL layer it's straightforward to use for people skilled in the Relational world. OrientDB adheres to the NoSQL movement even though it supports ACID Transactions and SQL as query language. In this way it's easy to start using it without having to learn too much new stuff. -
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RStudio
RStudio is an integrated development environment (IDE) for R
RStudio is a powerful, full-featured integrated development environment (IDE) tailored primarily for the R programming language but increasingly supportive of other languages like Python and Julia. It brings together console, editor, plotting, workspace, history, and file-management panes into a unified interface, helping data scientists, statisticians, and analysts to work more productively. The IDE is cross-platform: there are desktop versions for Windows, macOS and Linux, as well as a... -
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HStreamDB
HStreamDB is an open-source, cloud-native streaming database
...You can also replace message brokers with HStreamDB and everything you do with message brokers can be done better with HStreamDB. HStreamDB provides built-in support for event time-based stream processing. You can use your familiar SQL to perform basic filtering and transformation operations, statistics and aggregation based on multiple kinds of time windows and even joining between multiple streams. With connectors provided, you can easily integrate HStreamDB with other external systems, such as MQTT Broker, MySQL, Redis and ElasticSearch. More connectors will be added. -
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StarRocks
StarRocks is a next-gen sub-second MPP database for full analytics
StarRocks is the next generation of real-time SQL engines for enterprise analytics. Real-time analytics is notoriously difficult. Complex data pipelines and de-normalized tables have always been a necessary evil. Processing any updates or deletes once data arrives has not been possible- until now. StarRocks solves these challenges and makes real-time analytics easy. Get amazing query performance on Star or Snowflake Schemas directly. -
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POCO
Cross-platform C++ libraries for building network applications
The POCO C++ Libraries are powerful cross-platform C++ libraries for building network- and internet-based applications that run on desktop, server, mobile, IoT, and embedded systems. Whether building automation systems, industrial automation, IoT platforms, air traffic management systems, enterprise IT application and infrastructure management, security and network analytics, automotive infotainment and telematics, financial or healthcare, C++ developers have been trusting the POCO C++... -
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AWS SDK for pandas
Easy integration with Athena, Glue, Redshift, Timestream, Neptune
...The library abstracts efficient patterns like partitioning, compression, and vectorized I/O so you get performant data lake operations without hand-rolling boilerplate. It also supports Redshift, OpenSearch, and other services, enabling ETL tasks that blend SQL engines and Python transformations. Operational helpers handle IAM, sessions, and concurrency while exposing knobs for encryption, versioning, and catalog consistency. The result is a productive workflow that keeps your analytics in Python while leveraging AWS-native storage and query engines at scale. -
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Apache Seata
High-performance, open source distributed transaction solution
...Its architecture separates responsibilities into a global coordinator and per-service participants, so business services remain decoupled while transactions are orchestrated centrally. Multiple modes are supported—AT (automatic, SQL-based with undo logs), TCC (try-confirm-cancel), Saga (long-running compensation), and XA—letting architects choose between simplicity, control, and interoperability. The AT mode is notable for minimizing code changes: Seata captures before/after images of SQL updates and can roll back on failure to maintain atomicity across services. ... -
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ClickVisual
Log analytic and data visualize platform built on clickhouse
ClickVisual is a lightweight browser-based logs analytics and logs search platform for ClickHouse. -
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SageMaker Spark Container
Docker image used to run data processing workloads
...It provides high-level APIs in Scala, Java, Python, and R, and an optimized engine that supports general computation graphs for data analysis. It also supports a rich set of higher-level tools including Spark SQL for SQL and DataFrames, MLlib for machine learning, GraphX for graph processing, and Structured Streaming for stream processing. The SageMaker Spark Container is a Docker image used to run batch data processing workloads on Amazon SageMaker using the Apache Spark framework. The container images in this repository are used to build the pre-built container images that are used when running Spark jobs on Amazon SageMaker using the SageMaker Python SDK. ...
