Case in point: big data ecosystems, where numerous overlapping implementations rarely share components or use common APIs and layers. They also tend to lack standard wire protocols and each processing framework (think Spark, Presto and Flink) has its own data source API.
Open source is slouching towards individualization as every new framework or open source architecture has its own particular API, layers, or even wire protocol. In this article, Yaron Haviv explains why the open source community needs to work towards collaboration and standardization for the good of us all.
iguazio (Cool Vendors in Data Management) solves a pervasive problem of unifying different data workloads and data types — records, streams, objects and files — all within the same high-performance engine.
In this episode of Conversations in the Cloud, Yaron Haviv, Founder and CTO at iguazio discusses cloud native serverless processing with continuous analytics. iguazio tackles real-time big data processing by using continuous analytics to ingest, enrich, and analyze data, while simultaneously serving it to/from the same data repository.
Sentiment around containers often sounds like: “Oh, here’s my lightweight VM that happens to be called a Docker container, and I’m going to give it volume, and I’m going to create snapshots on that volume, and all that stuff,” Haviv stated.
According to iguazio co-founder and CTO Yaron Haviv, the platform can deliver 2 million transactions per second, with an average of 100 microsecond latency on 99% of transactions.