IBM Big Data
IBM solves this challenge with a zone architecture optimized for big data. The next generation architecture for big data and analytics delivers new business insights while significantly reducing storage and maintenance costs.
Data Management & Warehouse
Information Integration & Governance
Contact for Pricing
Small (<50 employees), Medium (50 to 1000 employees), Enterprise (>1001 employees)
IBM Big Data
IBM Big Data offers its users the next generation architecture for big data and analytics that delivers new business insights while significantly reducing storage and maintenance costs. IBM data scientists break big data into four dimensions such as volume, variety, velocity and veracity. A company will be able to stay on top of all the changes including, Hadoop-based analytics, streaming analytics, warehousing (including Big SQL), data asset discovery, integration as well as governance.Companies will be able to gain industry-leading database performance across multiple workloads while lowering administration, storage, development and server costs by using IBM Big Data. Also, realizing 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 is another feature from IBM’s data management and warehouse capabilities. Businesses will also be able to fully maximize the power of Apache Hadoop to the enterprise with application accelerators, analytics, visualization, development tools, performance and security features. With IBM Big Data’s content management capability, it enables the business to have comprehensive content lifecycle and document management with cost-effective control of existing and new types of content with scale, security and stability.In this day and age where in companies generate too many data in a single day will definitely require a Big Data management system. IBM Big Data can efficiently deliver real-time analytic processing on constantly changing data in motion and enable descriptive and predictive analytics to support real-time decisions. Users will be able to capture and analyze all data, all the time and just in time. And with stream computing, store less, analyze more and make better decisions faster.