Kinetica: Analytics database handling streaming data.

Drag and drop to generate data flows among your sources and targets.
Real-time SQL queries allow you to process, enrich, and analyze streaming data.
With its distributed parallel ingest capabilities, Kinetica is capable of doing high-speed ingestion on streaming data sets and complex analytics on streaming and historical data simultaneously.
It is possible to train TensorFlow models against data directly in Kinetica, or import pre-trained TensorFlow or “black box” models to execute inferences via batch processing, stream processing, or public web service.
Apache Spark™, a unified analytics engine that can handle large-scale data processing, is available.
Apache Spark delivers powerful for streaming and batch data.

Organizations can access worldwide accounting, liquidity management, marketing, and offer chain information with just one network connection.
The TreasuryPay product set streams global receivables information and provides instant accountancy together with cognitive services.
It is this is the innovative intelligence platform and insights platform open to global organizations.
It is possible to instantly provide enriched information to your complete global organization.
With TreasuryPay Instant™, now you can access actionable intelligence and global accountancy in real-time.
Kinetica is capable of doing powerful time series analysis such as for example aggregations, window functions, native track data analysis and inexact joins without having to send data to a separate

Financial Services & Investing

A breakthrough cloud service that simultaneously tracks telemetry across millions of data sources, with “real-time digital twins” — enabling deep, immediate introspection and state-tracking for a large number of devices.
The powerful UI makes deployment easy and displays aggregate analytics in real-time to increase situational awareness.

With Kinetica, you can explore the relationships between objects and events in the context of location and time, and visualize analysis at unrivaled speed and scale.
Kinetica is a distributed, memory-first OLAP database produced by Kinetica DB, Inc.
Kinetica is designed to use GPUs and modern vector processors to improve performance on complex queries across large volumes of real-time data.
Kinetica is perfect for analytics on streaming geospatial and temporal data.

• They will have decades of experience in mission critical enterprise workloads.
• In comparison, traditional risk management involves copying the transaction data to a separate cluster that runs risk models nightly.
• GPUdb was initially marketed for all of us military and intelligence applications, at Fort Belvoir for INSCOM.

This allows developers to easily create applications on a big scale.
Up to 95% of productivity can be increased by sharing, documenting, and cataloging data.
To handle privacy concerns and cover all of the gaps in open source technology, apply a data-centric security approach.

Network Security Assessment

Kylin can query at near constant speed no matter increasing data volumes by renovating the multi-dimensional cube, precalculation technology on Hadoop or Spark, and thereby achieving almost constant query speed.
Kylin reduces query latency from minutes right down to a fraction of a second, bringing online analytics back into big data.
Kylin can analyze a lot more than 10+ billion rows in less time when compared to a second.
Kylin connects Hadoop data to BI tools such as Tableau, PowerBI/Excel and MSTR.
Kylin is an Analytical Data Warehouse and offers ANSI SQL on Hadoop/Spark.

• The service provides integrations for hundreds third-party products, including databases, big data, DevOps, and SaaS applications.
• Data-level parallelism, or vectorization, accelerates analytics exponentially by performing exactly the same operation on different sets of data simultaneously, for maximum performance and efficiency.
• He completed his Master of Science in Information Technology at Southern New Hampshire University and has completed many certifications for big data and cloud technologies.

DataHUB4.0, a next-generation data historian, allows for real-time monitoring assets and systems across a network.
Analytics and data visualization tools are built-in to supply quick insights that enable you to see what is happening in virtually any facility, plant, or city at any time.
Equipment agnostic means that data can be integrated from any IoT device or sensor.
DataHUB4.0 may be the source of truth, and DataHUB4.0 stores data securely and reliably.
DataHub4.0 will not depend on costly IT infrastructure like traditional process historians.
DataHUB4.0 automatically checks data quality before it really is ingested and alerts teams when there is any problem.
It is ready for data analytics, AI, and data pre-processing, which eliminates data wrangling.

Google Cloud Dataflow

Kinetica prioritizes and manages data across VRAM, RAM, disk, and cold storage and can create external tables for dealing with data in HDFS, S3 and Azure.
Kinetica connects to a wide range of popular BI tools such as Tableau, Spotfire, PowerBI, ESRI, DBeaver and Grafana for real-time analytics withPostgres Wireline compatibility, or through the ODBC/JDBC connector.
The FAA uses Kinetica for Air Domain Analytics by fusing a huge selection of sensors in real-time for more accurate and faster tabs on our air space.
The simplest way to appreciate the options that Kinetica brings to large-scale geospatial analytics is to see it in action.
Defense and public safety organizations use Kinetica to provide real-time interactive dashboards for insights on rapidly evolving situtations.
This whitepaper from our friends at Atos explains the primary features and functionalities of the Atos HPC Software Suites and shares the company’s vision for the significant evolutions coming next in the HPC software arena.

HEAVY.AI originated from research at Harvard and MIT Computer Science and Artificial Intelligence Laboratory.
You can exceed traditional BI and GIS and extract high-quality information from large datasets without lag by leveraging modern GPU and CPU hardware.
To get a complete picture of what, when and where, unify and explore large geospatial or time-series data sets.
Combining interactive visual analytics, hardware accelerated SQL, advanced analytics & data sciences frameworks, you will find the opportunity and risk in your enterprise when it matters most.