Undoubtedly Big Data Analytics is adding a new set of strengths to the decision making capabilities of C-level executives of enterprises. Big Data Analytics is an integrated solution that needs a continuous support on data analysis. Today there is an increased demand for Big Data Analytics platforms and services that enable development, deployment, and management of big data. Being inspired by the increasing demand for Big Data Analytics, many mobile app development companies and other technology services companies extended their portfolio to Big Data Analytics services.
Most of the big data tools I am listing out below support the following areas of Big Data Analytics.
- Data Ingestion, Data Management, ETL, and Data Warehouse
- Hadoop System
- Stream Computing
- Data Integration
- Data Governance
- Content Management
- Analytics/Machine Learning
Top 10 Platforms Used for Big Data Analytics
- MapR Converged Data Platform
The MapR Converged Data Platform powers big data applications by integrating Hadoop, Spark, and Apache Drill with real-time database capabilities, global event streaming, and scalable enterprise storage. MapR platform provides enterprise grade security, reliability, and real-time performance. It reduces both the hardware and operational costs incurred to many important applications and data.
MapR supports numerous open source projects and uses industry-standard APIs. The MapR Distribution for Apache Hadoop allows organizations to get enterprise grade distributed data platform to store and process big data. MapR combines a wide range of Apache open source ecosystem projects, powering batch, interactive, or real-time applications.
- IBM Big Data
IBM Big Data platform includes many sophisticated tools and sub platforms that support a variety of tasks involved in Big Data Analytics. The tools are InfoSphere Streams, InfoSphere BigInsights, IBM Watson Explorer, IBM PureData, DB2 with BLU Acceleration, IBM Smart Analytics System, InfoSphere Information Server, and InfoSphere Master Data Management.
InfoSphere Streams is a high-performance computing platform that let users develop and reuse applications to quickly ingest, analyze, & correlate information as it comes from thousands of real-time sources.
IBM Big Data offers the next generation architecture for big data and analytics, which ensures reducing maintenance and storage costs. It covers all major areas of analytics like Hadoop-based analytics, streaming analytics, data asset discovery, data governance, data integration, and data warehousing.
- Amazon Web Services
Amazon Web Services offers three different products for Big Data Analytics: Amazon Athena, Amazon EMR, and Amazon Redshift.
Amazon Athena allows to run interactive queries directly against data in Amazon S3. Amazon EMR allows to deploy popular open source, big data frameworks like Apache Hadoop, Spark, Presto, HBase, and Flink. Amazon Redshift is a fully managed, petabyte-scale data warehouse, which allows to run even complex queries on massive collection of structured data.
- Cloudera Enterprise Big data
CDH is Cloudera’s key product, which is an open-source Hadoop based platform. Cloudera Enterprise Big data also includes advanced system management and data management tools. It is useful for working on data engineering and data science workloads, creating an operational or analytics database and it also allows to bring all of them in an enterprise data club.
- Hortonworks Data Platform
HDP is an enterprise-ready open source Apache Hadoop distribution platform based on a centralized architecture (YARN). HDP powers real-time customer applications and delivers true performance on big data analytics that enables effective decision making and innovation. HDP enables multi-workload data processing across a wide range of processing methods including batch, interactive and real-time.
HDP possesses a multi-faceted range of processing engines that help users to interact with the same data in different way, concurrently. Thus it enables applications to interact with the data in the best possible manner, from batch to interactive SQL or low latency access with NoSQL.
- HPE Big data
HPE has three different products cum solutions to help you leverage the power of Big Data Analytics, such as HPE Vertica Advanced Analytics, HPE IDOL, and HPE Haven on Demand.
Haven on Demand is a cloud based big data platform, which helps you analyze all sorts of data and use Big Data APIs to build next-gen apps and services.
- Intel Big data
Intel has a variety of products to support Big Data projects. The products include Intel Xeon processors, 10 Gigabit server adapters, SSDs, and the Intel Distribution. Businesses can effectively capture processes, analyze and store huge amounts of data with Intel’s architecture based advanced analytics solutions.
- DataStax Big data
DataStax Enterprise (DSE) is built on Apache Cassandra. DataStax introduced NoSQL Big Data platform called DataStax Enterprise (DSE) 3 with comprehensive enterprise-grade security features that is the first of its kind in the world. DSE 3 is a comprehensive integrated big data platform that blends a production-certified version of Cassandra with Apache Solr and Apache Hadoop.
Conclusion:
Apart from these platforms, there are many market-driven Big Data analytics platforms that include Informatica PowerCenter Big Data Edition, Kognito Analytical Platform, Data Meter and Good Data. In case if you’re looking to adopt Big Data Analytics for your business, you’re suggested choose Big Data Analytics services company, so they can help you unearth the hidden opportunities and mitigate invisible risks in Big Data Analytics.
informative, thanks..