Remove Big Data Tools Remove Blog Remove Bytes
article thumbnail

Data Engineering Annotated Monthly – May 2022

Big Data Tools

RocksDB is a storage engine with a key/value interface, where keys and values are arbitrary byte streams written as a C++ library. It can store data virtually everywhere, for example in memory or on any kind of permanent storage device. And yes, it pays attention to correctness and effectiveness when storing data.

article thumbnail

Data Engineering Annotated Monthly – May 2022

Big Data Tools

RocksDB is a storage engine with a key/value interface, where keys and values are arbitrary byte streams written as a C++ library. It can store data virtually everywhere, for example in memory or on any kind of permanent storage device. And yes, it pays attention to correctness and effectiveness when storing data.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

100+ Kafka Interview Questions and Answers for 2023

ProjectPro

This blog brings you the most popular Kafka interview questions and answers divided into various categories such as Apache Kafka interview questions for beginners, Advanced Kafka interview questions/Apache Kafka interview questions for experienced, Apache Kafka Zookeeper interview questions, etc. What do you understand about quotas in Kafka?

Kafka 40
article thumbnail

50 PySpark Interview Questions and Answers For 2023

ProjectPro

Python has a large library set, which is why the vast majority of data scientists and analytics specialists use it at a high level. If you are interested in landing a big data or Data Science job, mastering PySpark as a big data tool is necessary. Is PySpark a Big Data tool?

Hadoop 52
article thumbnail

100+ Big Data Interview Questions and Answers 2023

ProjectPro

If you're looking to break into the exciting field of big data or advance your big data career, being well-prepared for big data interview questions is essential. Get ready to expand your knowledge and take your big data career to the next level! Steps for Data preparation.