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Paypal Open-Sources JunoDB: Its Distributed Key-Value Store

June 14, 2023
in AI & Technology
Reading Time: 4 mins read
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Paypal Open-Sources JunoDB: Its Distributed Key-Value Store
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Paypal recently open-sourced JunoDB, a distributed key-value store built on RocksDB. Daily, JunoDB, PayPal’s highly available and security-focused database, processes 350 billion requests.

PayPal’s wide variety of applications relies heavily on JunoDB, a distributed key-value store. JunoDB is used for virtually every critical backend service at PayPal, including authentication, risk assessment, and transaction settlement. Data may be cached and accessed quickly from apps using JunoDB, reducing the strain on backend services and relational databases. JunoDB, however, is not an ordinary NoSQL database. It was developed to meet PayPal’s specific requirements. Thus, it can simultaneously manage many concurrent users and connections without slowing down. Originally built in single-threaded C++, it has been rewritten in Golang to take advantage of parallel processing and many cores. 

The JunoDB architecture is a dependable and extensible system that prioritizes ease of use, scalability, security, and flexibility. Proxy-based design simplifies development by abstracting away complex logic and setup from applications and allowing for linear horizontal connection scaling. When expanding or contracting clusters, JunoDB uses consistent hashing to split data and reduce the amount of data that must be moved. JunoDB uses a quorum-based protocol and a two-phase commit to guarantee data consistency and ensure there is never any downtime for the database.

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Protecting information both in transit and at rest is a high priority. Hence TLS support and payload encryption are implemented. Finally, JunoDB’s flexibility and ability to adapt over time are guaranteed by its pluggable storage engine design, which makes it simple to switch to new storage technologies as they become available.

The core of JunoDB is made up of three interdependent parts:

  1. The JunoDB proxy allows application data to be easily stored, retrieved, and updated, thanks to the JunoDB client library’s provided API. With support for languages including Java, Golang, C++, Node, and Python, the JunoDB thin client library can be easily integrated with programs built in various languages.
  2. Client queries and replication traffic from remote sites are processed by proxy instances of JunoDB that are controlled by a load balancer. Each proxy establishes a connection to all JunoDB storage server instances, and routes request to a set of storage server instances according to the shard mapping stored in ETCD.
  3. JunoDB uses RocksDB to store data in memory or persistent storage upon receiving an operation request from a proxy.

JunoDB maintains high levels of accessibility and system responsiveness while supporting many client connections. It also manages data expansion and maintains high read/write throughput even as data volume and access rates rise. To achieve six 9s of system availability, JunoDB uses a mix of solutions, including data replication inside and outside data centers and failover mechanisms.

JunoDB provides exceptional performance at scale, managing even the most intensive workloads with response times in the millisecond range and without disrupting the user experience. In addition, JunoDB offers a high throughput and low latencies, enabling applications to scale linearly without compromising performance.

Users can get the source code for JunoDB, released under the Apache 2 license, on GitHub. PayPal produced server configuration and client development tutorial videos to aid developers’ database use. The team plans to include a Golang client and a JunoDB operator for Kubernetes in the future. 


Check Out The Reference Article. Don’t forget to join our 23k+ ML SubReddit, Discord Channel, and Email Newsletter, where we share the latest AI research news, cool AI projects, and more. If you have any questions regarding the above article or if we missed anything, feel free to email us at [email protected]

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Tanushree Shenwai is a consulting intern at MarktechPost. She is currently pursuing her B.Tech from the Indian Institute of Technology(IIT), Bhubaneswar. She is a Data Science enthusiast and has a keen interest in the scope of application of artificial intelligence in various fields. She is passionate about exploring the new advancements in technologies and their real-life application.


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