Year 2017 seems to be an exciting time for big data professionals. Big data vendor landscape is evolving rapidly and at the same time products that are on the offering are more stable and matured.
However, from all the mess that is created in the big data space over the past few years, where are we gearing towards?
Answer is "Big Data Analytics(BDA)". Machine learning applications on top of big data are catching up fast in the vendors landscape of big data. That is what the key take away from some of the studies done in this field as in the reference link.
What is big data analytics?
The term is not something new, it is analytics applied on big data to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful information that can
help organizations make more-informed business decisions.
These applications help to analyze growing volumes of structured transaction data, plus other forms of data that are often left untapped by conventional business intelligence (BI) and analytics programs.
Leading big data analytics platforms and softwares
I have listed some of the leading vendors that provide big data analytic platform. This list is not in any ranking order. For more recent updates on this information, you can also check the reference links shared.
List of popular big data analytics vendors:
Microsoft has come up with array of products to cater big data analytics needs. With many of its Azure cloud solutions, Microsoft is one of the leading vendors in the market.
The applications can be built using any language, tool or framework and can integrated with other public cloud applications in the IT environment. One of the biggest advantage of these products is that they are very well integrated and thus offer integrated complete solution for customers.
IBM is one of the most competent vendors offerring solutions for Big data and analytics. Their product suite includes: InfoSphere Streams , InfoSphere BigInsights , IBM Watson Explorer , IBM PureData powered by Netezza technology , DB2 with BLU Acceleration , IBM Smart Analytics System , InfoSphere Information Server and InfoSphere Master Data Management.
IBM's big data and analytics capabilities include :
- Data Management & Warehouse: Gain industry-leading database performance across multiple workloads while lowering administration, storage, development and server costs; Realize extreme speed with capabilities optimized for analytics workloads such as deep analytics, and benefit from workload-optimized systems that can be up and running in hours.
- Hadoop System: Bring the power of Apache Hadoop to the enterprise with application accelerators, analytics, visualization, development tools, performance and security features.
- Stream Computing: Efficiently deliver real-time analytic processing on constantly changing data in motion and enable descriptive and predictive analytics to support real-time decisions. Capture and analyze all data, all the time, just in time. With stream computing, store less, analyze more and make better decisions faster.
- Content Management: Enable comprehensive content lifecycle and document management with cost-effective control of existing and new types of content with scale, security and stability.
- Information Integration & Governance: Build confidence in big data with the ability to integrate, understand, manage and govern data appropriately across its lifecycle.
SAP HANA is in-memory big data platform and provides massively parallel processing database.
Bigdata Analytics solutions include the Predictive Analytics and Text Analytics solutions. Advanced processing capabilities such as predictive (60+ algorithms), data quality, and graph provide deeper insights. Built in business function libraries help to push down more logic inside the database accelerating application performance and reducing data movements.
Bigdata solution from HP includes HP HAVEn and HP Vertica. HP HAVEn is a platform comprised of software, services, and hardware. Big Data of any type either structured and unstructured can be analyzed to lead to powerful strategic insights. HP Vertica Dragline let organizations store their data in a cost effective manner, and provide capabilities to explore it quickly using SQL based tools.
Oracle has range of big data analytic products that can fulfil multiple requirements of customers. Critical component of these offering includes products such as Oracle Big Data Appliance, Oracle Exadata Database Machine and Oracle Exalytics In-Memory Machine.
These are engineered Systems which are pre-integrated to reduce the cost and complexity of IT infrastructures. The database include Oracle Database, Oracle NoSQL Database, MySQL and MySQL Cluster, Oracle Event Processing, Oracle NoSQL Database and Oracle Coherence, Oracle Endeca Information Discovery and in database analytics.
SAS is the industry leader for analytics and offers range of solutions for analysing big data. SAS Bigdata Analytics solution portfolio includes Credit Scoring for SAS Enterprise Miner, SAS High-Performance Data Mining, SAS Model Manager, SAS Scoring Accelerator, SAS Text Miner and SAS Visual Statistics.
Amazon Web Services(AWS) is one of the most popular cloud service and widely used across th eindustry. AWS provides a broad range of services to help you build and deploy big data analytics applications quickly and easily. As it is a cloud offering, it is cost effective and has advantage of ease of access.
AWS gives you fast access to flexible and low cost IT resources, so you can rapidly scale virtually any big data application including data warehousing, clickstream analytics, fraud detection, recommendation engines, event-driven ETL, serverless computing, and internet-of-things processing.