
Tricount
Settle Up
Splid
Spliit
YNAB
ihatemoney
Splitser
Splitwise is a free tool for friends and roommates to track bills and other shared expenses, so that everyone gets paid back. On the web, iPhone, and Android!

Mockaroo
Generate Data
DataMaker
MockBlast
SynthForge IO
MockTurtle.net
Neosync
Turn SQL schemas into realistic test data in seconds. Perfect for testing, demos, and development.
Which is more popular?
Website, pricing, platforms and company facts side by side.
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|---|---|---|
| Website | splitwise.com | ddltodata.com |
| Pricing | — | |
| Company | — | Startup from the United States · 2025 |
| Listed in |
In their own words, as submitted to SaaSHub.


No description of Splitwise yet.
DDL to Data is a developer tool that automatically generates realistic test data from SQL schemas. Simply paste your CREATE TABLE statement and get back JSON data with smart type detection—column names like "email" produce real email formats, "phone" produces phone numbers,...
What each product offers, as listed by its team.


Possible disadvantages
An editorial look at what each product does well and who it suits.


Overall verdict
Why this product is good
Recommended for
Overall verdict
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Walkthroughs and reviews on video.
Splitwise - iPhone App Review! [2020]
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How often each product is chosen within a category, 0–100% relative to the other.


As answered by people managing Splitwise and DDL to Data.
DDL to Data's answer:
No LLM, no prompts, no AI costs. DDL to Data uses deterministic pattern-matching — not machine learning — to generate realistic test data from your SQL schema in milliseconds. It's fast, predictable, and won't hallucinate. Column named "email" produces an email, "phone" produces a phone number. Same schema, same structure, every time. Plus it handles foreign key relationships to generate referentially-intact data across multiple tables.
DDL to Data's answer:
Unlike AI-powered tools, DDL to Data has zero token costs, sub-second response times, and deterministic output, critical for CI/CD pipelines. Unlike Faker libraries, it requires zero configuration: paste your CREATE TABLE and get intelligent, type-aware data without writing any setup code. It also supports multiple output formats (JSON, CSV, SQL, Parquet, Excel) and can seed data directly into your PostgreSQL database.
DDL to Data's answer:
Backend developers, QA engineers, and DevOps teams who need realistic test data for database testing, seeding dev environments, CI/CD pipelines, and product demos. Particularly useful for teams who want a reliable, no-config utility that just works, without adding AI dependencies to their infrastructure.
DDL to Data's answer:
Every new project meant the same tedious ritual: write the schema, then manually create arrays of fake emails, phone numbers, and timestamps. Over and over. It struck me that the schema already contains everything needed to generate realistic data, column names are semantic. "email" means email, "created_at" means timestamp. So I built an API that does the obvious thing automatically, without any AI complexity
DDL to Data's answer:
FastAPI (Python) backend with PostgreSQL and SQLAlchemy. Next.js 14 frontend with TypeScript and Tailwind CSS. Hosted on AWS with Docker containers, and CircleCI for CI/CD.
DDL to Data's answer:
Currently in public beta and growing organically. Early adopters include indie developers and small engineering teams using it for local development and automated testing pipelines.
Share your experience with using Splitwise and DDL to Data. For example, how are they different and which one is better?
External articles and on-site reviews we used to compare the two products.


Splitwise is among the most commonly used group payment apps that can easily keep a systematic record of all your informal debts including restaurant bills, travel expenses, cost of accommodation, and much more. With...
Splitwise employs an intelligent algorithm to calculate the exact amount owed by each user. It shows who paid for what, how much amount was paid by each member, and any outstanding balances. Furthermore, the...
For example, shared items like appetizers would be split among the entire group or just a few people in the group. The app can handily accommodate large parties by allowing you to add up to 10 people to each group....
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