Best Hadoop Architectures

Informatica Big Data Parser enables access to the most difficult data and file formats in Hadoop, reducing the time and cost of developing data handlers by 70 percent. It enables IT organizations to efficiently manage industry standards, binary documents, and hierarchical data. Big Data Parser provides a unique development environment for lean data integration. With this software, your IT organization can view data samples within Big Data Parser Studio and understand their structure and layout through a set of integrated tools

IBM Netezza Analytics is an embedded, purpose-built, advanced analytics platform that empowers analytic enterprises to meet and exceed their business demands. As features, it can predict with more accuracy, deliver predictions faster and respond rapidly to changes.

IBM Db2® Big SQL is an enterprise-grade, hybrid ANSI-compliant SQL-on-Hadoop engine, delivering massively parallel processing (MPP) and advanced data query. Db2 Big SQL offers a single database connection or query for disparate sources such as Hadoop HDFS and WebHDFS, RDMS, NoSQL databases and object stores. Benefit from low latency, high performance, security, SQL compatibility and federation capabilities to do ad hoc and complex queries.

The BlueData EPIC™ (Elastic Private Instant Clusters) software platform solves the infrastructure challenges and limitations that can slow down and stall Big Data deployments. With EPIC software, you can spin up Hadoop and Spark clusters – with the data and analytical tools that your data scientists need – in minutes rather than months. Leveraging the power of containers, BlueData EPIC makes it easier, faster, and more cost-effective to deploy Big Data infrastructure and applications—including Hadoop, Spark, Kafka, Cassandra, and more— whether on-premises or in the public cloud. Your data scientists and analysts can use the tools they prefer. You can run it with any shared storage environment, so you don’t have to move your data. And it delivers the enterprise-grade security and governance that your IT teams require. With the BlueData EPIC software platform, you can provide a highly flexible and secure Big-Data-as-a-Service environment to enable faster time-to-insights and faster time-to-value – now available either on-premises or on AWS.

Cask Data Application Platform (CDAP) is the first Unified Platform for Big Data. It provides standardization and deep integrations with diverse Hadoop technologies allowing companies to focus on application logic and insights, rather than infrastructure and integration. The platform is 100% open-source, highly extensible, and delivers enterprise-class features to help accelerate time to build, deploy, and manage data-centric applications & data lakes on Hadoop and Spark. There are 3 extensions packaged with CDAP: Cask Hydrator, Cask Wrangler and Cask Tracker. CDAP Extensions are self-service, purpose-built applications on CDAP designed to solve common and critical big data challenges. Cask Hydrator for data pipelines, Cask Wrangler for data wrangling and Cask Tracker for data discovery and metadata. CDAP removes barriers to innovation as an extensible and future-proof platform that provides consistency across environments and easily integrates with existing MDM, BI, and security solutions.

Splice Machine is an application platform built to power predictive applications that manage operational processes, large-scale IoT infrastructures, analytical processing and machine learning. It is a Hybrid RDBMS that can be delivered as a cloud service, or used on premise through our Enterprise Edition or Community Edition.

A self-managing and self-optimizing data platform. Constantly analyzes and learns about your big data platform’s usage through combination of heuristics and machine learning. Provides actionable Alerts, Insights and Recommendations (AIR) to optimize reliability, performance and costs. Automatically enacts policies through a number of Cloud Agents to eliminate the need for repetitive manual actions

QueryIO is a Hadoop-based SQL and Big Data Analytics solution, used to store, structure, analyze and visualize vast amounts of structured and unstructured Big Data. It is especially well suited to enable users to process unstructured Big Data, give it a structure and support querying and analysis of this Big Data using standard SQL syntax. QueryIO enables you to leverage the vast and mature infrastructure built around SQL and relational databases and utilize it for your Big Data Analytics needs.

Lily Enterprise sits on top of the Cloudera or Hortonworks Hadoop platforms, and considers the entire Hadoop stack and all data streams, including data warehouses, data lakes, CRM systems, mobile/online or social media activities, contact center applications and POS systems. Lily combines them into one cumulative, organized and actionable solution, and delivers real-time execution of predictive analytical models to help create individual customer profiles, Lily Customer DNA, to give organizations the most accurate, atomic-level view of their customers.

Customers worldwide choose XCrypt Data Encryption solutions for use in high performance, high availability and seamlessly scalable data environments. XCrypt Data Encryption solutions are designed to function with near-zero latency to support the most demanding deployment requirements, including high-speed transactions, in-memory databases, and real-time, web-based applications.

Argyle Data has had the privilege of working with global leaders and visionaries on their strategies for revenue threat analytics, big data, and machine learning. What consistently comes up is that best-in-class carriers know the revenue threats that they have been attacked with in the past. What they don’t know is how to prepare for future attacks that will likely incorporate new types and methods of revenue threats. What is critical to understand is that a) criminals are continually innovating; b) each subscriber will have many devices, many channels, and many potential attack points; and c) we need a better way to detect new fraud and protect customers and carriers in this new world – today in 2015, not in 2020. This requires an effective strategy for the use of big data and machine learning in the areas of:Fraud Threats Analytics apps for identifying threats from various types of domestic fraud and roaming fraudProfit Threats Analytics apps for identifying threats from arbitrage, negative margin, high usage, and bill shockSLA Threats Analytics apps for identifying threats from network vulnerabilities and from roaming partners not meeting their SLA windowsForensic Threats Graph analysis application for analyzing 1st to 5th degrees of separation between data assets

Liberate your data, by making it possible for any data analyst in your company to access and rapidly analyze data in the Hadoop data lake, without burdening your IT team. The Altiscale Insight Cloud handles both real-time and batch analytics, and connects easily to your favorite BI solutions.