Enes Akar
CEO at Upstash
Palo Alto, California, United States
Summary
🤩
Rockstar🎓
Top SchoolEnes Akar is a seasoned distributed systems engineer and entrepreneur with 14 years of experience building cloud-first infrastructure and real-time data platforms. As cofounder and CEO of Upstash and former CTO of Hazelcast Cloud, he blends hands-on backend development (notably contributions to core Hazelcast data loading and write-behind logic) with product and company leadership. He’s repeatedly focused on serverless, edge, in-memory data grids and streaming systems—Kafka, Redis, Hazelcast—bringing pragmatic solutions for low-latency, scalable workloads. Based in Palo Alto, he pairs an MBA and a CS background with a founder’s mindset, often anchoring technical decisions in operational simplicity and cost-effective cloud design.
14 years of coding experience
13 years of employment as a software developer
MBA, MBA at Boğaziçi University
Stackoverflow
3,123reputation
239kreached
46answers
24questions
Github Skills (17)
hadoop-mapreduce10
mapster10
distributed-systems10
mapreduce10
java10
javas10
mapr10
data-structure9
concurrency9
data-structures9
hazelcast6
in-memory-database6
distributed-cache6
distributed-computing6
hbase6
Programming languages (14)
Github contributions (5)
hazelcast/hazelcast
Mar 2012 - Feb 2017
Hazelcast is a unified real-time data platform combining stream processing with a fast data store, allowing customers to act instantly on data-in-motion for real-time insights.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:880 commits, 59 PRs, 75 pushes in 4 years 11 months
Contributions summary:Enes focused on implementing core features related to loading and handling data for the Hazelcast unified real-time data platform. The contributions involved modifying core classes such as `MapContainer.java` and `DefaultRecordStore.java` with the implementation of methods like `loadAll`, and the integration of write-behind methods. The user's work impacted the core logic of data management within the Hazelcast ecosystem, specifically by modifying how data is loaded from underlying storage and managed within the system.
computationstream-processingbigtablereal-timestreaming-data
upstash/kafka-examples
Dec 2021 - Apr 2022
Sample applications implemented with Serverless Kafka
Contributions:1 review, 17 commits, 4 PRs in 4 months
kafkaserverlessconnectorupstash
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