Manetu’s data privacy platform manages millions of identities and unlocks new use cases with YugabyteDB

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Manetu offers a secure data privacy platform that helps consumers and businesses manage personal data.
Its microservices application needed fine-grained transaction support, secondary indexes, and triplestore capabilities, all while being able to scale to billions of encrypted identities.
With YugabyteDB, Manetu not only achieves global scale and high performance, it also enabled new time series use cases that were not possible with other databases.

Manetu puts consent management in consumers’ hands, enabling consumers to control their data and enterprises to comply with data privacy laws.

New laws in California, Europe and elsewhere require that businesses allow consumers to access the data held about them. Manetu’s Consumer Privacy Management platform includes a consumer-facing portal that gives consumers control and automates fulfillment of these requests; as well as a business-facing portal that simplifies enterprise compliance by tying together all sources of PII into a single, secure, state-of-the-art privacy vault.

The Manetu platform is made up of microservices, written in a mix of Clojure and Go on Kubernetes. Examples of these services include an attribute service, the core of the platform where the PII is encrypted and stored, and an activity log service that provides an activity graph to consumers and administrators. These services are powered by YugabyteDB.

With its current design, the Manetu platform is proven at nearly 70 million identities and architected to scale to hundreds of millions, and into billions over time. Manetu is trusted by customers and partners worldwide, including Hedera Hashgraph, Odgers Berndtson, Pickstar, and more.


  • With their previous Cassandra experience, Manetu knew they needed a Cassandra-like model to support a high performance RDF triplestore for the attribute service, but was concerned Cassandra wouldn’t be able to scale without operational complexity
  • Capabilities like fine-grained transaction support and usable secondary indexes were required for their attribute service, but were not supported in Cassandra
  • Their new activity log service required a time series database, but due to the high cardinality of data, various time series systems were evaluated but couldn’t scale to meet the ingest rate or required latency to generate the graphs they needed to present in their dashboard

Key Database Requirements

  • High scalability and ease of use
  • Ability to perform transactions and utilize secondary indexes at scale
  • Ability to manage data with high cardinality
  • Flexibility to support multiple use cases
  • High performance and low latency
We were not able to use a commercial off-the-shelf time-series database for our use case. When I tested at scale, the system completely fell apart; other databases couldn't keep up with the cardinality of our data. The only solution that worked was to implement a custom time series index on top of YugabyteDB, and it works really well.
Greg Haskins
Chief Technology Officer,
Manetu has built a custom RDF triple-store featuring transparent cryptography, individual keys for every relationship, and de-identification features to serve our customer's privacy needs from the cloud. Serving this type of data securely and at scale while maintaining SLAs is non-trivial. However, YugabyteDB's high performance, compatibility with the larger CQL ecosystem, and inherent ease for maintaining highly available multi-AZ deployments and ‘push button’ elastic scale made it an easy choice to underpin our offering, and allowed us to build a world-class service. It also helped that they have a program for startups!

YugabyteDB Solution

96 total cores and
24 TB of data
3 node clusters in
single region, multi-
zone deployments
Yugabyte + Kafka
as primary
persistent layer
Easily deployed
and managed in
Manetu’s AWS VPC

Technical results

  • Easy to scale out with transactions and secondary indexes
  • Effectively manages time series workloads with high-cardinality datasets
  • High performance reads and writes in a microservices, CQRS architecture
  • Able to ingest high volumes of data quickly during onboarding events (bringing on new customers and the identity data they hold)

Business Results

  • Flexibility to support multiple use cases, including sensitive PII and time series data
  • Comprehensive multi-region deployment options to enable compliance across the globe as business grows
  • Future-proofing business for billions of identities
  • Responsive technical support
Conor Allen
Head of Product,
We’re not aware of another database that would allow us to scale to every person in the world. We have global aspirations and YugabyteDB as part of our architecture could see us well down the road into billions of identities and managing events for all of them.