Best Big Data Software for Alteryx

ANSI SQL allows you to analyze petabytes worth of data at lightning-fast speeds with no operational overhead. Analytics at scale with 26%-34% less three-year TCO than cloud-based data warehouse alternatives. You can unleash your insights with a trusted platform that is more secure and scales with you. Multi-cloud analytics solutions that allow you to gain insights from all types of data. You can query streaming data in real-time and get the most current information about all your business processes. Machine learning is built-in and allows you to predict business outcomes quickly without having to move data. With just a few clicks, you can securely access and share the analytical insights within your organization. Easy creation of stunning dashboards and reports using popular business intelligence tools right out of the box. BigQuery's strong security, governance, and reliability controls ensure high availability and a 99.9% uptime SLA. Encrypt your data by default and with customer-managed encryption keys

Secure and manage the data lifecycle, from Edge to AI in any cloud or data centre. Operates on all major public clouds as well as the private cloud with a public experience everywhere. Integrates data management and analytics experiences across the entire data lifecycle. All environments are covered by security, compliance, migration, metadata management. Open source, extensible, and open to multiple data stores. Self-service analytics that is faster, safer, and easier to use. Self-service access to multi-function, integrated analytics on centrally managed business data. This allows for consistent experiences anywhere, whether it is in the cloud or hybrid. You can enjoy consistent data security, governance and lineage as well as deploying the cloud analytics services that business users need. This eliminates the need for shadow IT solutions.

MongoDB is a distributed database that supports document-based applications and is designed for modern application developers. No other database is more productive. Our flexible document data model allows you to ship and iterate faster and provides a unified query interface that can be used for any purpose. No matter if it's your first customer, or 20 million users worldwide, you can meet your performance SLAs in every environment. You can easily ensure high availability, data integrity, and meet compliance standards for mission-critical workloads. A comprehensive suite of cloud database services that allows you to address a wide range of use cases, including transactional, analytical, search, and data visualizations. Secure mobile apps can be launched with native, edge to-cloud sync and automatic conflicts resolution. MongoDB can be run anywhere, from your laptop to the data center.

IBM® SPSS® Statistics software is used by a variety of customers to solve industry-specific business issues to drive quality decision-making. The IBM® SPSS® software platform offers advanced statistical analysis, a vast library of machine learning algorithms, text analysis, open-source extensibility, integration with big data and seamless deployment into applications. Its ease of use, flexibility and scalability make SPSS accessible to users of all skill levels. What’s more, it’s suitable for projects of all sizes and levels of complexity, and can help you find new opportunities, improve efficiency and minimize risk.

All your data, analytics, and AI in one unified platform. Databricks is powered by Delta Lake. It combines the best data warehouses with data lakes to create a lakehouse architecture that allows you to collaborate on all your data, analytics, and AI workloads. We are the original developers of Apache Spark™, Delta Lake, and MLflow. We believe open source software is the key to the future of data and AI. Your business can be built on an open, cloud-agnostic platform. Databricks supports customers all over the world on AWS, Microsoft Azure, or Alibaba cloud. Our platform integrates tightly with the cloud providers' security, compute storage, analytics and AI services to help you unify your data and AI workloads.

SAP HANA is an in-memory database with high performance that accelerates data-driven decision-making and actions. It supports all workloads and provides the most advanced analytics on multi-model data on premise and in cloud.

Businesses struggle to find answers as data volumes increase faster than ever. Teradata Vantage™, solves this problem. Vantage uses 100 per cent of the data available to uncover real-time intelligence at scale. This is the new era in Pervasive Data Intelligence. All data across the organization is available in one place. You can access it whenever you need it using preferred languages and tools. Start small and scale up compute or storage to areas that have an impact on modern architecture. Vantage unifies analytics and data lakes in the cloud to enable business intelligence. Data is growing. Business intelligence is becoming more important. Four key issues that can lead to frustration when using existing data analysis platforms include: Lack of the right tools and supportive environment required to achieve quality results. Organizations don't allow or give proper access to the tools they need. It is difficult to prepare data.

The Unified Analytics Warehouse. The Unified Analytics Warehouse is the best place to find high-performing analytics and machine learning at large scale. Tech research analysts are seeing new leaders as they strive to deliver game-changing big data analytics. Vertica empowers data-driven companies so they can make the most of their analytics initiatives. It offers advanced time-series, geospatial, and machine learning capabilities, as well as data lake integration, user-definable extensions, cloud-optimized architecture and more. Vertica's Under the Hood webcast series allows you to dive into the features of Vertica - delivered by Vertica engineers, technical experts, and others - and discover what makes it the most scalable and scalable advanced analytical data database on the market. Vertica supports the most data-driven disruptors around the globe in their pursuit for industry and business transformation.

You can query billions upon billions of rows with an in-memory columnar database and MPP architecture. Queries are distributed across all cluster nodes, allowing for linear scaling and advanced analytics. The fastest database for data analytics is made up of MPP, columnar storage, and in-memory. You can analyze data anywhere it is stored, whether you are using SaaS, cloud, hybrid, or on-premises deployments. Automatic query tuning reduces overhead and maintenance. You get more power for a fraction of the normal infrastructure costs with seamless integrations and performance efficiency. This social networking company was able to increase its performance by using smart, in-memory query processing. They processed 10B data sets per year. A single data repository and speed-engine to accelerate critical analytics, improving patient outcomes and the bottom line.

Apache Hadoop is a software library that allows distributed processing of large data sets across multiple computers. It uses simple programming models. It can scale from one server to thousands of machines and offer local computations and storage. Instead of relying on hardware to provide high-availability, it is designed to detect and manage failures at the application layer. This allows for highly-available services on top of a cluster computers that may be susceptible to failures.

Apache Spark™, a unified analytics engine that can handle large-scale data processing, is available. Apache Spark delivers high performance for streaming and batch data. It uses a state of the art DAG scheduler, query optimizer, as well as a physical execution engine. Spark has over 80 high-level operators, making it easy to create parallel apps. You can also use it interactively via the Scala, Python and R SQL shells. Spark powers a number of libraries, including SQL and DataFrames and MLlib for machine-learning, GraphX and Spark Streaming. These libraries can be combined seamlessly in one application. Spark can run on Hadoop, Apache Mesos and Kubernetes. It can also be used standalone or in the cloud. It can access a variety of data sources. Spark can be run in standalone cluster mode on EC2, Hadoop YARN and Mesos. Access data in HDFS and Alluxio.

Your apps can be freed. Reduce complexity in your operations. Software proficiency is essential to win in today's business world. How can you increase the feature velocity of the workloads that power your company? Or run and manage modernized workloads in any cloud. VMware Tanzu, when used with VMware Pivotal Labs, enables you to transform your team and your applications while simplifying operations across multicloud infrastructure: on-premises and public cloud.