About
The Java™ Programming Language is a general-purpose, concurrent, strongly typed, class-based object-oriented language. It is normally compiled to the bytecode instruction set and binary format defined in the Java Virtual Machine Specification. In the Java programming language, all source code is first written in plain text files ending with the .java extension. Those source files are then compiled into .class files by the javac compiler. A .class file does not contain code that is native to your processor; it instead contains bytecodes — the machine language of the Java Virtual Machine1 (Java VM). The java launcher tool then runs your application with an instance of the Java Virtual Machine.
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About
Nim is a statically typed compiled systems programming language. It combines successful concepts from mature languages like Python, Ada and Modula. Nim generates native dependency-free executables, not dependent on a virtual machine, which are small and allow easy redistribution. Nim's memory management is deterministic and customizable with destructors and move semantics, inspired by C++ and Rust. It is well-suited for embedded, hard-realtime systems. Modern concepts like zero-overhead iterators and compile-time evaluation of user-defined functions, in combination with the preference of value-based datatypes allocated on the stack, lead to extremely performant code. Support for various backends: it compiles to C, C++ or JavaScript so that Nim can be used for all backend and frontend needs.
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About
SQL is a domain-specific programming language used for accessing, managing, and manipulating relational databases and relational database management systems.
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About
dbt Labs helps data teams transform raw data into trusted, analysis-ready datasets faster. With dbt, analysts and engineers can collaborate on version-controlled SQL models, enforce testing and documentation standards, and deploy transformations reliably at scale. Built on modern software engineering best practices, dbt brings transparency and governance to every step of the data transformation workflow.
Thousands of companies, from startups to Fortune 500 enterprises, rely on dbt to reduce data debt, increase trust, and accelerate insights across their organization. Whether you’re scaling data operations or just getting started, dbt empowers your team to move from raw data to actionable analytics with confidence.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
Developers looking for a Programming Language solution
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Audience
Programming Language solution for DevOps
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Audience
Developers and database admins
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Audience
SQL users looking for a ETL solution to engineer data transformations
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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API
Offers API
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API
Offers API
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Screenshots and Videos |
Screenshots and Videos |
Screenshots and Videos |
Screenshots and Videos |
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Pricing
Free
Free Version
Free Trial
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Pricing
Free
Free Version
Free Trial
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Pricing
Free
Free Version
Free Trial
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Pricing
$100 per user per user/ month
Free Version
Free Trial
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Reviews/
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Reviews/
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationOracle
docs.oracle.com/javase/8/docs/technotes/guides/language/index.html
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Company InformationNim
nim-lang.org
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Company InformationSQL
Founded: 1974
sourceforge.net/software/product/SQL/
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Company Informationdbt Labs
Founded: 2016
United States
www.getdbt.com
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Alternatives |
Alternatives |
Alternatives |
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Categories |
Categories |
Categories |
Categoriesdbt Labs powers the transformation layer of modern data pipelines. Once data has been ingested into a warehouse or lakehouse, dbt enables teams to clean, model, and document it so it’s ready for analytics and AI. With dbt, teams can: - Transform raw data at scale with SQL and Jinja. - Orchestrate pipelines with built-in dependency management and scheduling. - Ensure trust with automated testing and continuous integration. - Visualize lineage across models for faster impact analysis. By embedding software engineering practices into pipeline development, dbt Labs helps data teams build reliable, production-grade pipelines — reducing data debt and accelerating time to insight. dbt Labs brings rigor and scalability to data preparation by enabling teams to clean, transform, and structure raw data directly in the warehouse. Instead of siloed spreadsheets or manual workflows, dbt uses SQL and software engineering best practices to make data preparation reliable, repeatable, and collaborative. With dbt, teams can: - Clean and standardize data with reusable, version-controlled models. - Apply business logic consistently across all datasets. - Validate outputs through automated tests before data is exposed to analysts. - Document and share context so every prepared dataset comes with lineage and definitions. By treating data preparation as code, dbt Labs ensures that prepared datasets aren’t just quick fixes — they’re trusted, governed, and production-ready assets that scale with the business. dbt Labs modernizes the “T” in ETL. Instead of relying on legacy pipelines or black-box transformations, dbt empowers data teams to build, test, and document transformations directly inside the data warehouse or lakehouse. With dbt, teams can: - Transform raw data into analytics-ready models using SQL and Jinja. - Ensure reliability with built-in testing, version control, and CI/CD. - Standardize workflows across teams with reusable models and shared documentation. - Leverage modern platforms like Snowflake, Databricks, BigQuery, and Redshift for scalable transformation. By focusing on the transformation layer, dbt Labs helps organizations shorten pipeline development cycles, reduce data debt, and deliver trusted insights faster — complementing ingestion and loading tools in a modern ELT stack. |
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Big Data Features
Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates
Data Lineage Features
Database Change Impact Analysis
Filter Lineage Links
Implicit Connection Discovery
Lineage Object Filtering
Object Lineage Tracing
Point-in-Time Visibility
User/Client/Target Connection Visibility
Visual & Text Lineage View
Data Preparation Features
Collaboration Tools
Data Access
Data Blending
Data Cleansing
Data Governance
Data Mashup
Data Modeling
Data Transformation
Machine Learning
Visual User Interface
ETL Features
Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control
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Integrations
AWS Cloud9
Alan AI
Amazon SageMaker Unified Studio
AppWarp
Arch
BBEdit
Codebashing
Cofactr
DashO
Gemini 2.5 Pro Preview (I/O Edition)
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Integrations
AWS Cloud9
Alan AI
Amazon SageMaker Unified Studio
AppWarp
Arch
BBEdit
Codebashing
Cofactr
DashO
Gemini 2.5 Pro Preview (I/O Edition)
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Integrations
AWS Cloud9
Alan AI
Amazon SageMaker Unified Studio
AppWarp
Arch
BBEdit
Codebashing
Cofactr
DashO
Gemini 2.5 Pro Preview (I/O Edition)
|
Integrations
AWS Cloud9
Alan AI
Amazon SageMaker Unified Studio
AppWarp
Arch
BBEdit
Codebashing
Cofactr
DashO
Gemini 2.5 Pro Preview (I/O Edition)
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