With the increase in the volume of BigData and the great growth in cloud computing, cutting-edge BigData Analytics Tools have become critical to achieving meaningful data analysis. In this blog, we will look at the best BigData Analytics tools and their essential features.
Tools for Big Data Analytics
Apache Storm:
Apache Storm is a free and open-source large data processing system. Apache Storm is another Apache product that provides a real-time framework for data stream processing and may be used with any programming language. It provides a fault-tolerant, distributed real-time processing system. With capabilities for real-time calculation. Storm scheduler spreads workload across several nodes based on topology and works well with The Hadoop Distributed File System (HDFS).
Features:
- It can process one million 100-byte messages per second per node.
- Storm guarantees that each unit of data will be processed at least once.
- Excellent horizontal scalability
- Fault tolerance is included.
- Auto-restart after an accident
- Clojure-written
- It is compatible with the Direct Acyclic Graph (DAG) topology.
- JSON format is used for output files.
- It offers a wide range of applications, including real-time analytics, log processing, ETL, continuous computation, distributed RPC, and machine learning.
Apache CouchDB
It is a free and open-source, cross-platform, document-oriented NoSQL database with a scalable architecture. It is written in the concurrency-oriented programming language Erlang. Couch DB saves data in JSON documents that may be viewed over the web or obtained via JavaScript queries. It provides distributed scaling as well as fault-tolerant storage. It enables data access by defining the Couch Replication Protocol.
Features:
- CouchDB is a single-node database that functions similarly to other databases.
- It enables the operation of a single logical database server on any number of servers.
- It employs the widely used HTTP protocol and the JSON data format.
- Inserting, updating, retrieving, and deleting documents is a breeze.
- The JavaScript Object Notation (JSON) format is translatable across languages.
Apache Spark
Spark is another well-known and open-source big data analytics solution. Spark features over 80 high-level operators that make it simple to create parallel programs. It is used to process huge datasets in a variety of businesses.
Features:
- It enables an application to run in a Hadoop cluster up to 100 times quicker in memory and ten times faster on disc.
- It provides lightning-fast processing support for sophisticated analytics, as well as the ability to integrate with Hadoop and current Hadoop data.
- It has built-in APIs in Java, Scala, or Python. Spark has in-memory data processing capabilities, which are much quicker than MapReduce’s disc processing.
- Furthermore, Spark integrates with HDFS, OpenStack, and Apache Cassandra, both in the cloud and on-premises, bringing another layer of flexibility to your company’s big data operations.
Splice Machine
It is a tool for large data analytics. Their architecture is adaptable to public clouds like AWS, Azure, and Google.
Features:
- It can scale dynamically from a few to thousands of nodes, enabling applications at various scales.
- Every query to the scattered HBase regions is automatically evaluated by the Splice Machine optimizer.
- Lower management, deploy more quickly and reduce risk.
- Consume fast streaming data while developing, testing, and deploying machine learning models.
Azure HDInsight
It is a cloud-based Spark and Hadoop service. It offers two types of big data cloud services: Standard and Premium. It provides the organization with an enterprise-scale cluster on which to run its big data tasks.
Features:
- Analytics that are dependable and have an industry-leading SLA
- It provides enterprise-level security and monitoring.
- Safeguard data assets by extending on-premises security and governance controls to the cloud.
- A platform with a high level of efficiency for developers and scientists
- Integration with the most popular productivity programs.
- Deploy Hadoop in the cloud without having to buy new gear or pay any other upfront fees.
Leave a Reply