Software Alternatives, Accelerators & Startups

DUMMY DATABASE VS Google Cloud Datastore

Compare DUMMY DATABASE VS Google Cloud Datastore and see what are their differences

DUMMY DATABASE logo DUMMY DATABASE

Generate and manage synthetic datasets easily with DUMMY DATABASE

Google Cloud Datastore logo Google Cloud Datastore

Cloud Datastore is a NoSQL database for your web and mobile applications.
  • DUMMY DATABASE Main page
    Main page //
    2025-08-09
  • DUMMY DATABASE Tables edit
    Tables edit //
    2025-08-09
  • DUMMY DATABASE Events sequence
    Events sequence //
    2025-08-09
  • DUMMY DATABASE SQL editor
    SQL editor //
    2025-08-09
  • DUMMY DATABASE ERD
    ERD //
    2025-08-09

Dummy Database is built to solve a simple, yet annoying problem โ€” generating realistic test datasets quickly, without writing scripts or juggling Excel files.

Itโ€™s 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 Cloud Datastore Landing page
    Landing page //
    2023-09-12

DUMMY DATABASE

$ Details
free
Platforms
Web
Release Date
2024 October
Startup details
Country
Serbia
City
Novi Sad
Founder(s)
Igor Bobritskii
Employees
1 - 9

DUMMY DATABASE features and specs

  • Relations Datasets Generation
    Automatically create realistic, interlinked datasets that preserve relational integrity between tables โ€” perfect for simulating multi-table databases for testing, analytics, and demos.
  • Sequence of Events
    Define and generate realistic event chains with time dependencies, probabilities, and conditional paths โ€” ideal for modeling user journeys, workflows, or process mining scenarios.
  • Built-in SQL Editor
    Instantly query, filter, and transform generated datasets without leaving the platform โ€” no need for external tools or database setup.

Google Cloud Datastore features and specs

  • Scalability
    Google Cloud Datastore can automatically scale to handle large amounts of data and high read/write loads, making it suitable for applications with growing data needs.
  • Fully Managed
    As a fully managed service, Google Cloud Datastore eliminates the need for managing servers, software patches, and replication, allowing developers to focus on building applications.
  • High Availability
    Datastore provides strong consistency for reads and writes and is designed to maintain availability even in case of entire data center outages.
  • Flexible Data Model
    The schemaless nature of Datastore allows for a flexible data model that can easily adapt to changes in application requirements.
  • Integration with Google Cloud Platform
    Datastore seamlessly integrates with other Google Cloud Platform services, which simplifies the process of building end-to-end solutions.

Possible disadvantages of Google Cloud Datastore

  • Complex Query Language
    Datastore Query Language (GQL) can be less intuitive compared to SQL, which may pose a learning curve for developers accustomed to traditional relational databases.
  • Eventual Consistency for Queries
    While Datastore offers strong consistency for entity lookups by key, queries must be specifically configured for strong consistency, otherwise they might return eventually consistent data.
  • Cost
    As usage scales, costs can increase, particularly for applications with high write loads or those requiring many transactional operations, which might be a consideration for budget-conscious projects.
  • Limited Relational Capabilities
    Datastore is a NoSQL database, which means it lacks some of the relational features like joins and complex transactions that developers might expect from a SQL database.
  • Index Management
    Managing indexes can become complex, as every query in Datastore requires a corresponding index, and poorly planned indexes can lead to increased storage costs and slower query performance.

Category Popularity

0-100% (relative to DUMMY DATABASE and Google Cloud Datastore)
Databases
11 11%
89% 89
Synthetic Data
100 100%
0% 0
NoSQL Databases
0 0%
100% 100
Datasets
100 100%
0% 0

Questions & Answers

As answered by people managing DUMMY DATABASE and Google Cloud Datastore.

What makes your product unique?

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.

Why should a person choose your product over its competitors?

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

How would you describe the primary audience of your product?

DUMMY DATABASE's answer

  • 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's the story behind your product?

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

Which are the primary technologies used for building your product?

DUMMY DATABASE's answer

Python, Flask, HTML, CSS, Bootstrap, Redis, PostgreSQL, JavaScript

User comments

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Social recommendations and mentions

Based on our record, Google Cloud Datastore seems to be more popular. It has been mentiond 7 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.

DUMMY DATABASE mentions (0)

We have not tracked any mentions of DUMMY DATABASE yet. Tracking of DUMMY DATABASE recommendations started around Aug 2025.

Google Cloud Datastore mentions (7)

  • Using Google Cloud Firestore with Django's ORM
    A long time ago, a fork of Django called โ€œDjango-nonrelโ€ experimented with the idea of using Djangoโ€™s ORM with a non-relational database; what was then called the App Engine Datastore, but is now known as Google Cloud Datastore (or technically, Google Cloud Firestore in Datastore Mode). Since then a more recent project called "django-gcloud-connectors" has been developed by Potato to allow seamless ORM integration... - Source: dev.to / about 2 years ago
  • How to deploy flask app with sqlite on google cloud ?
    In that case use Cloud Datastore (aka Firestore in Datastore Mode). It's a NoSQL db that was initially targeted just for GAE (you needed to have a GAE App even if empty to use it) but that requirement has been relaxed. Source: over 3 years ago
  • Is Cloud Run a good choice for a portfolio website?
    As u/SierraBravoLima said - If you don't really need containerization, you can go with Google App Engine (Standard). If you need to store data, GAE will work with cloud datastore which has a large enough free tier. Source: about 4 years ago
  • Help! Difference between native and datastore
    Datastore mode had its start in App Engine's early days (launched in 2008), where its Datastore was the original scalable NoSQL database provided for all App Engine apps. In 2013, Datastore was made available all developers outside of App Engine, and "re-launched" as Cloud Datastore. In 2014, Google acquired Firebase for its RTDB (real-time database). Both teams worked together for the next 4 years, and in 2017,... Source: over 4 years ago
  • I'm a dev ID 10 T please help me
    Database: datastore should be very cheap, or you could just output as csv text and copy into Google Sheets (free!). Source: over 4 years ago
View more

What are some alternatives?

When comparing DUMMY DATABASE and Google Cloud Datastore, you can also consider the following products

Mockaroo - A realistic data generator to test your app

MarkLogic Server - MarkLogic Server is a multi-model database that has both NoSQL and trusted enterprise data management capabilities.

DataConstruct - We fake it till you make it!

Datomic - The fully transactional, cloud-ready, distributed database

Data Creator - Data generator that can create a table filled with pseudo-random content.

Valentina Server - Valentina Server is 3 in 1: Valentina DB Server / SQLite Server / Report Server