Big Data in Modern Cloud
Cloud-based big data solutions give businesses a competitive advantage in our data-centric world.
IBM
IBM offers a suite of big data solutions, including Db2 Big SQL, a hybrid SQL engine for Hadoop that enables easy data querying across the enterprise. In partnership with Hortonworks, IBM provides seamless integration with various data sources like HDFS, RDBMS, and NoSQL databases. Additionally, IBM's Big Replicate ensures continuous availability and data consistency, while IBM Analytics for Apache Spark delivers fast processing of large data volumes in a secure, managed environment.
Azure
Azure empowers businesses to make informed decisions by analyzing massive amounts of data in real time. With services like HDInsight, which supports frameworks such as Hadoop, Spark, Hive, and Kafka, Azure enables insights that drive intelligent actions to enhance customer engagement and increase revenue.
Apache Spark's Computational Engine
Apache Spark is a vital computational engine for scheduling, distributing, and monitoring applications across clusters. It comprises four main components: Spark-SQL, Spark Streaming, Spark MLib, and Graph-X, catering to diverse analytics needs.
RabbitMQ
RabbitMQ, preferred over Apache Kafka in certain workspaces, provides a flexible messaging system by hiding the sender and receiver from each other. It ensures secure communication through TLS encryption and supports clustering solutions for enhanced reliability.
D3.js for Dynamic Data Visualization
D3.js, a JavaScript library for visualization, helps bring data to life using SVG, Canvas, and HTML. It is widely used in various applications, including sensor data visualization and monitoring household water usage.
AWS Greengrass
AWS Greengrass runs local compute, messaging, and data caching for connected devices. It enables devices to connect, run AWS Lambda functions, and sync data, facilitating efficient IoT gateway management.
Services
Nestack provides comprehensive AWS big data services with certified architects and developers.
Certified AWS Expertise
Nestack boasts a team of certified solution architects and developer associates specializing in AWS. This expertise ensures the deployment of scalable and cost-effective big data applications on AWS's pay-as-you-use infrastructure.
Amazon EMR
Nestack leverages Amazon EMR to provide a comprehensive Hadoop framework integrated with Apache Spark, HBase, Presto, and Flink. These frameworks interact seamlessly with AWS data stores like S3 and DynamoDB, enabling Nestack to offer solutions such as log analysis, web indexing, data transformations (ETL), machine learning, financial analysis, and bioinformatics.
Amazon Elasticsearch
Nestack utilizes Amazon Elasticsearch Service to simplify the deployment, security, operation, and scaling of Elasticsearch for log analytics, full-text search, and application monitoring.
Interactive Query Service
The service facilitates data analysis in S3 using standard SQL. Its serverless architecture ensures easy management, and integration with AWS Glue and Data Catalog enables unified metadata creation across various services.
Amazon Kinesis Suite
Nestack employs Amazon Kinesis Firehose for loading massive volumes of streaming data, enabling real-time data analytics with existing BI tools. Amazon Kinesis Analytics aids in analyzing streaming data using standard SQL, while Amazon Kinesis Streams allows for the creation of custom applications for streaming data analysis.
Big data storage and Databases
Nestack provides a range of storage and database solutions, including Amazon S3 for object storage, Amazon DynamoDB for NoSQL databases, HBase on Amazon EMR for big data processing, Amazon Aurora for relational databases, and Amazon RDS for managed relational database services.
Business Intelligence
Nestack leverages Amazon QuickSight to deliver rich BI functionality, assisting clients with data visualizations, ad-hoc analysis, and obtaining quick business insights.