Big Data In Modern Cloud
At Nestack we have staff of Data Scientist, The Data Analyst, The Data Architect, The Statistician, The Data Administrator, The Business Analyst, Data and Analyst Manager who can help you to gather, manage, analyze, and evaluate your big data to really understand what it's all saying.
Amazon Web Services:
Nestack has solution architect and developer associate who are certified from amazon web services.As you know AWS provide wide range of services to deploy big data applications. This scalable and pay what you use infrastructure helps to save lot of money.
Amazon EMR: Provide Hadoop framework along with Apache Spark, HBase, Presto and Flink these frameworks can interact with AWS data stores like S3,Dynamodb.Nestack will provide solutions like log analysis, Web indexing, Data transformations (ETL), Machine learning, financial analysis and bioinformatics.
Amazon Elasticsearch: This service make it easy to deploy, secure, operate and scale elasticsearch for log analytics, full text search and application monitoring.
Interactive Query Service: It helps to analyse data in S3 using standard SQL. It has serverless architecture so it is very easy to manage.On top of it is integrated with AWS Glue, Data catalog.This will allow you to create unified metadata across various services.It crawl data source and then populate your catalog.
Amazon Kinesis Firehose: This will help to load massive volume of streaming data and then enables to perform real time data analytics with existing BI tools
Amazon kinesis Analytics: This will help to easily analyze streaming data with standard SQL.
Amazon Kinesis Streams: This will help to create custom application to analyse streaming data.
IBM: IBM Provides Db2 Big SQL, To provide this service IBM and Hortonworks partnered.It provides easy data querying across the enterprise with Hybrid SQl engine for Hadoop.It can connect data sources like HDFS, RDBMS and noSQL databases. IBM also provides Big Replicate this will provide continuous availability, Performance and guaranteed data consistency. IBM also provides service called IBM analytics for Apache Spark, it process large data volumes with great speed in hosted managed and secure environment.
Azure: Azure deliver better solution and make better decisions by analyzing massive amounts of data in real time. Target insight you need to deliver intelligent actions that will improve customer engagement, increase revenue, and lower costs. Nestack has azure experts that have Good hands on Azure services like HDInsight which uses popular open source frameworks such as Hadoop,Spark, Hive, LLAP, Kafka, Storm, R and more.It also Provide support for Data Lake Analytics it process Big data Jobs It starts instantly and it is pay per job service.
Big data storage and Databases:
- Amazon S3
- Nosql (Amazon Dynamodb)
- Hbase on Amazon EMR
- Amazon Aurora
- Relational database (Amazon RDS)
Business Intelligence: Amazon provide Quick Sight it provides rich BI functionality. It can help you with visualizations, perform Ad-hoc analysis and this will help you to get quick business insight. Nestack Solution architect are certified and they will provide service to perform any AWS big data related service.
IOT: Apache Spark is a computational engine which is responsible for scheduling, distributing, and monitoring applications consisting of many computational tasks across many worker machines, or a computing cluster.Apache Spark has four main components which are Spark-SQL,Spark Streaming,Spark Mllib,Graph-X.
RabbitMQ: RabbitMQ and apache Kafka has pretty same use but In our workspace the RabbitMQ is more fissible. The Main use for rabbitMq is it hide sender and receiver from each other. In RabbitMQ client can communicate through TCP/IP port 5672.To secure this connection we can encrypt it using TLS with RabbitMQ.We can also authenticate it using peer certificate. It will take 104ms to produce and consume 1000000 messages. RabbitMQ comes with clustering solution that why we prefer it over kafka.
AWS Greengrass (IOT Gateway): It runs local compute, messaging and data cashing for connected devices. AWS Green grass Connect devices and can run AWS lambda functions and this will help to create data sync.