Table of Contents

Top 10 Big Data Frameworks In 2022

Table of Contents
Big Data Framework

Have you ever wondered how to choose the best big data engine? The market for big data software is humongous, competitive and full of software that does very similar things. So, what big data framework will be the best pick in 2022?

#1 Hadoop

Most big data software is either built around or compliant with Hadoop. Hadoop is great for reliable, scalable, distributed calculations.

Hadoop uses an intermediary layer between an interactive database and data storage. Its performance grows according to the increase of the data storage space. Hadoop is great for customer analytics, enterprise projects and creation of data lakes or for any large-scale batch processing task that doesn’t require immediacy or an ACID-compliant data storage.

But despite Hadoop’s definite popularity, more advanced alternatives are gradually coming to the market.

#2 MapReduce – Hadoop native data processing engine

MapReduce is a search engine of the Hadoop framework. It is a good choice for businesses analyzing archived information, making regular reports which require decision making and other use cases not aiming at instant results. MapReduce provides the automated paralleling of data, efficient balancing and failsafe performance.

#3 Apache Spark

Spark is a powerful open source data analytics cluster computing framework. It has become very popular because of its speed, in tired of computing and better data access because of its in-memory caching it’s a library that enables developers to create complex applications faster and better.

#4 Apache Hive

Apache Hive is a data warehouse system built on top of Apache Hadoop that facilitates easy data summarization. Hive can be integrated with Hadoop as a server part for the analysis of large data values. Here is a benchmark showing Hive on Tez speed performance against the competition (lower is better).

Hive remains one of the most used Big data analytics frameworks ten years after the initial release.

#5 Apache Storm

Apache Storm is used by big companies like Yelp, Yahoo, Alibaba and some others. The key features of Storm are scalability and prompt restoring ability after downtime. Storm provides better latency than both Flink and Spark. However, it has worse throughput.

#6 Apache Samza

Apache Samza is a stateful stream processing big data framework that was co-developed with Apache Kafka. Kafka provides data serving, buffering and fault tolerance. The duo is intended to be used where quick single stage processing is needed. This big data processing framework was developed for LinkedIn and is also used by eBay and TripAdvisor for fraud detection.

#7 Apache Flink

Apache Flink is an open source platform for stream and batch data processing. Blink has been designed to run in all common cluster environments, perform computations at in-memory speed and at any scale.

#8 Apache Heron

Twitter developed Heron as a new generation replacement for Storm. It is intended to be used for real-time spam detection, ETL tasks and trend analytics. Its design goals include low latency, good and predictable scalability and easy administration. Benchmarks show a significant improvement over Storm.

#9 Apache Kudu

Kudu was designed to simplify some complicated pipelines in the Hadoop ecosystem. It runs on commodity hardware, is horizontally scalable and supports highly available operations. This framework is currently used for market data fraud detection on Wall Street. Kudu is picked by Xiaomi for collecting error reports mainly because of its ability to simplify and streamline data pipeline to improve query and analytics speeds.

#10 Presto – SQL query engine

Presto is a faster, flexible alternative to Apache Hive for smaller tasks. It’s an adaptive, flexible query tool for a multi-tenant data environment with different storage types.

To sum up, it’s safe to say there is no single best option among the data processing frameworks and our experienced, Hybrid solutions with different tools work best. The variety of offers on the big data framework market allows every company to pick the most appropriate tool for their task.
Do you need experts’ help to choose the most appropriate tech stack? We at EZtek provide tech consulting and engineering services to top brands worldwide. Contact us now!


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