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Open Source Synthetic Data Orchestration
A developer-first way to create anonymized or synthetic data and sync it across all environments for high-quality local, stage and CI testing
Generate Data for Any Schema
Tabular
Generate statistically consistent synthetic data for a single data frame or table.
Relational
Generate statistically consistent synthetic data for a relational database while maintaining referential integrity.
Built for Security and Scalability
Neosync is built for teams of all sizes and ships with features that put security and compliance teams of all sizes at ease. Whether you're an enterprise who needs an air-gapped deployment or a startup looking to get started quickly, Neosync can help.
Complete referential integrity
Neosync automatically handles and preserves your data's referential integrity.
Retries
Neosync handles automatically handles retries in the case of an error during the sync process.
Scheduling
Run jobs ad-hoc, pause existing jobs or schedule jobs to run on any cadence you decide.
Scalable
Neosync's async pipeline is horizontally scalable making it a great choice for bigger data sets.
Security
Neosync comes with RBAC out of the box and is designed to be multi-tenant for teams deploying on-prem.
Audit
Neosync ships with audit controls so security and compliance teams have a full audit trail over the system.
Synthetic Data Orchestration Built for Developers
Automatically sync all of your data stores, from local databases to s3 buckets with anonymized, production data to safely build and test your applications and services.
APIs to automatically sync local databases with prod to keep them up to date.
Locally develop against safe,anonymized, production-like data
Subset your data using a custom query to shrink it to fit locally.
Use the Neosync CLI to back up to an old copy or pull the latest
fill_local_db.py
1...
2 schedule = "0 23 * * *"
3 haltOnNewColAdd = True
4 jobRes, err = jobclient.CreateJob(ctx, connect.NewRequest({
5 'AccountId': accountId,
6 'JobName': 'prod-to-stage',
7 'ConnectionSourceId': prodDbResp['Msg']['Connection']['Id'],
8 'DestinationSourceIds': [
9 stageDbResp['Msg']['Connection']['Id'],
10 s3Resp['Msg']['Connection']['Id'],
11 ],
12 'CronSchedule': schedule,
13 'HaltOnNewColumnAddition': haltOnNewColAdd,
14 'Mappings': [
15 {
16 'Schema': 'public',
17 'Table': 'users',
18 'Column': 'account_number',
19 'Transformer': JobMappingTransformer.custom_account_number,
20 },
21 {
22 'Schema': 'public',
23 'Table': 'users',
24 'Column': 'address',
25 'Transformer': JobMappingTransformer.address_anonymize,
26 },
27 ],
28 }))
29 if err:
30 raise Exception(err)
31...0
0
Use GitOps to hydrate your CI databases with synthetic data
Automatically hydrate your CI database with safe, production-like data
Declaratively define a step in your CI pipeline with Neosync
Protect sensitive data from your CI pipelines
Subset your database to reduce your
Fully customizable Transformers
Anonymize, mask or generate data using a transformer from our library of pre-built tranformers or write your own transformation logic in code.
Pre-built Transformers
Choose from our library of pre-built transformers
Custom Transformers
Create your own transformer for when you need bespoke logic
Powerful subsetting
Subsetting allows you to filter your source database so that you can easily reproduce bugs and data errors and shrink your production database so that it fits locally. Neosync maintains full referential integrity of your data automatically.
Synthetic Data meets GitOps
Neosync is built with DevOps and infrastructure teams in mind. Use frameworks you know like terraform to manage your Neosync infrastructure and even create new jobs.
Manage your test infrastructure in code
Easily create jobs, connections, mappings and more
Audit and track changes across teams
Centralize your configurations in one place
terraform.tf
1resource "neosync_job" "staging-sync-job" {
2 name = "prod-to-stage"
3
4 source_id = neosync_postgres_connection.prod_db.id
5 destination_ids = [
6 neosync_postgres_connection.stage_db.id,
7 neosync_s3_connection.stage_backup.id,
8 ]
9
10 schedule = "0 23 * * *" # 11pm every night
11
12 halt_on_new_column_addition = false
13
14 mappings = [
15 {
16 "schema" : "public",
17 "table" : "users",
18 "column" : "account_number",
19 "transformer" : "custom_accout_number",
20 },
21 {
22 "schema" : "public",
23 "table" : "users",
24 "column" : "address",
25 "transformer" : "address_anonymize"
26 },
27 ]
28 }0
0
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