Google BigQuery
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Looker
Jupyter
Presto DB
Amazon EMR
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Rakam
DUMMY DATABASE
Mockaroo
DataConstruct
Data Creator
Datamade
Random Data
Dummy Database is built to solve a simple, yet annoying problem โ generating realistic test datasets quickly, without writing scripts or juggling Excel files.
Itโs designed for: - Developers needing dummy databases for prototyping & testing. - Analysts and BI specialists preparing demo dashboards. - QA engineers creating data scenarios for testing. - SQL learners who want practice datasets on demand.
What makes it special? - Create from simple tables to full relational databases with PK/FK. - 35+ data types including Numbers, Dates, Names, Booleans, etc. - Unique Event Sequences โ simulate user actions and workflows. - Advanced data controls โ outliers, nulls, repeats, distributions. - ERD visualization to map relationships. - Built-in PostgreSQL editor to query generated data. - Export as CSV, XLSX, SQL DDL, or full ZIP. - Free up to 10,000 records per table for registered users โ no paywalls or limits.
Google BigQuery DUMMY DATABASENo DUMMY DATABASE videos yet. You could help us improve this page by suggesting one.
DUMMY DATABASE's answer:
A free, all-in-one data generation platform that builds everything from simple tables to full relational databases with advanced controls, unique event sequences, ERD visualization, built-in SQL querying, and multiple export formats โ no limits, no paywalls.
DUMMY DATABASE's answer:
Unlike other data generators, DUMMY DATABASE gives you full relational database creation, unique event simulations, advanced control over every field, built-in SQL querying, and generous free limits โ so you can go from idea to test-ready data without restrictions, subscriptions, or hidden fees
DUMMY DATABASE's answer:
DUMMY DATABASE's answer:
Began as a project for myself to be able to have custom datasets for testing purpose I've decided that it could be useful for wider audience and finalized it as a full-stack web project
DUMMY DATABASE's answer:
Python, Flask, HTML, CSS, Bootstrap, Redis, PostgreSQL, JavaScript
Based on our record, Google BigQuery seems to be more popular. It has been mentiond 47 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
We migrated the analytics layer to Google BigQuery. Same queries that timed out in PostgreSQL now run in under 2 seconds. But not everything belongs in BigQuery โ we initially moved too aggressively and actually reverted some queries back when the added complexity wasn't justified. Our rule of thumb: if a query scans hundreds of thousands of rows or involves complex time-series aggregations, BigQuery. Everything... - Source: dev.to / 3 months ago
Google BigQuery - For large-scale data processing and SQL-based analysis. - Source: dev.to / 4 months ago
Data Pipelines usually read from tables that change over time. Most of these tables are stored in a data warehouse like Amazon Redshift or Google BigQuery. Rows are added or removed. Backfills happen. A column gets renamed or its meaning changes. Even when teams snapshot data, those snapshots are often implicit, not recorded as part of the pipeline run itself. - Source: dev.to / 5 months ago
SQL endures because it's the non-negotiable interface for relational data. Enterprise data storage still relies heavily on relational databases despite new alternatives. What makes SQL valuable for learners is transferabilityโwhile dialects differ across PostgreSQL, SQL Server, and BigQuery, the fundamentals stay consistent. - Source: dev.to / 7 months ago
Within classic cloud data warehouses, Google BigQuery presents a different pricing model. Its on-demand, per-terabyte-scanned pricing can be cost-effective for sporadic forensic queries. But it carries the risk of a runaway query where a single mistake leads to a massive bill. - Source: dev.to / 8 months ago
Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.โWhat is Apache Spark?
Mockaroo - A realistic data generator to test your app
Looker - Looker makes it easy for analysts to create and curate custom data experiencesโso everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.
DataConstruct - We fake it till you make it!
Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.
Data Creator - Data generator that can create a table filled with pseudo-random content.
