opaque-sql
An encrypted data analytics platform (by mc2-project)
mc2
A Platform for Secure Analytics and Machine Learning (by mc2-project)
Our great sponsors
opaque-sql | mc2 | |
---|---|---|
2 | 8 | |
176 | 291 | |
0.6% | 0.7% | |
1.1 | 0.7 | |
about 1 year ago | about 1 year ago | |
Scala | C++ | |
Apache License 2.0 | Apache License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
opaque-sql
Posts with mentions or reviews of opaque-sql.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-08-10.
-
How to Run Spark SQL on Encrypted Data
Introducing Opaque SQL, an open-source platform for securely running Spark SQL queries on encrypted data. Built by top systems and security researchers at UC Berkeley, the platform uses hardware enclaves to securely execute queries on private data in an untrusted environment.
-
Announcing MC²: Securely perform analytics and machine learning on confidential data
The MC2 Compute Services: MC2 offers several compute services: these include Spark SQL, distributed XGBoost, and secure aggregation for federated learning. All are intended to run in a primarily untrusted environment, such as a cluster of machines hosted on a public cloud, that has support for trusted execution environments (hardware enclaves). Data is encrypted in transit using a client key and only ever decrypted inside hardware enclaves, providing the previously mentioned security guarantees for data-in-use. For all compute services, MC2 leverages the Open Enclave SDK, a project intended to provide a consistent API for a variety of different enclave architectures.
mc2
Posts with mentions or reviews of mc2.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-04-15.
-
Intel deprecates SGX on Core series processors
Analytics and ML on confidential data are some interesting server side use cases. See the MC2 open source project, for example: https://github.com/mc2-project/mc2
-
How to Run Spark SQL on Encrypted Data
Check out more blog posts on how to securely process data with MC² Project. We would love your contributions ✋ and support ⭐! Please check out the Github repo to see how you can contribute. No contribution is too small.
- Show HN: MC² – Secure collaborative analytics and ML
- MC2: Secure Collaborative Analytics and ML
-
Announcing MC²: Securely perform analytics and machine learning on confidential data
MC2 is a platform for running secure analytics on data that stays encrypted even when in use. By doing so, the project also enables secure collaboration among multiple organizations, where individual data owners can use our platform to jointly analyze their collective data without revealing it to one another. To learn more and to see the individual projects’ documentation, visit our landing page.
-
Secure collaborative analytics and ML on encrypted data using MC²
Whoops. My bad: https://github.com/mc2-project/mc2
-
[P] Secure collaborative analytics and ML on encrypted data using MC²
Our team @ UC Berkeley has been working on a platform for secure analytics and machine learning called MC2 -- and today we are excited to announce the initial release v0.1 of the platform! With MC2, you can take encrypted data and run various analytics and machine learning workloads at near processor speeds, while keeping the data confidential. MC2 also enables secure collaboration -- mutually distrustful data owners can jointly analyze / train models on their data, but without revealing their data to each other. Github: https://github.com/mc2-project/mc2
What are some alternatives?
When comparing opaque-sql and mc2 you can also consider the following projects:
kyuubi - Apache Kyuubi is a distributed and multi-tenant gateway to provide serverless SQL on data warehouses and lakehouses.
delphi - A Cryptographic Inference Service for Neural Networks
secure-xgboost - Secure collaborative training and inference for XGBoost.
incubator-gluten - Gluten is a middle layer responsible for offloading JVM-based SQL engines' execution to native engines.
cerebro - Cerebro: A platform for Secure Coopetitive Learning
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
secure-aggregation - Secure aggregation for federated learning using enclaves
federated-xgboost - Federated gradient boosted decision tree learning