Data is Big and Data is Fast

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paper-icon-miniSolving the Fast Data Problem for the Cloud
Integrating VoltDB and the IBM Softlayer Cloud Computing Platform delivers up to 5X the performance of Amazon Web Services. Learn more in this data sheet.

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videos-icon-miniCustomer Coffee Talk: deltaDNA’s Chris Wright
Chris Wright, co-founder and CTO of deltaDNA, discusses how the ability to make real-time decisions creates a win-win for gaming organizations.

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videos-icon-miniVoltJolt Presents Scott Jarr
In this VoltJolt video, VoltDB co-founder and Chief Strategy Officer Scott Jarr talks about the power of data that is both fast and relevant.

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videos-icon-miniFast Data is Breaking Your Architecture
VoltDB provides the transformational database technology to make Smart Data Fast. Listen to Ryan Betts, VoltDB’s Chief Technology Officer, speak on today’s Big Data, Fast Data challenge.

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videos-icon-miniThe Fast Data – Big Data Challenge
Peter Vescuso, VoltDB’s Chief Marketing Officer, speaks about the Internet of Things, Big Data, Fast Data, and what VoltDB offers.

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Fast Data, coming from the explosion of data in mobile, social, devices/Internet of Things (IoT), needs to be acted on immediately, while Big Data requires deep analytics. Although stream processing systems can perform basic rules-based processing of Fast Data, only VoltDB is able to interact with data, make per event decisions and provide meaningful analytics.

VoltDB is a ground-up redesign of the relational database for today’s growing data challenges. Architected by Dr. Mike Stonebraker, VoltDB is scalable to easily handle fast data, powerful to make it smart, and reliable and fault tolerant in both back-room and cloud environments.

Fast Data has five key processes that must be managed.


Ingest & Interact on Fast-moving Streams of Inbound Data

Systems that handle Fast Data must be able to ingest unlimited streams of data from highly-concurrent sources and interact with that data in real time. VoltDB delivers unparalleled data ingestion speeds while supporting the real-time, in-memory analysis needed by Big Data applications.


Organize Data in Real Time

As Fast Data is received it must be organized so it can be acted on. Organizing data makes it possible to update online sessions in real time; group data by device type, location or time; filter duplicates; augment incoming data, and identify incomplete or corrupt results.


Analyze on a Per-event Basis

As data is ingested and organized it is analyzed on a per-event basis. Events may include updating streaming aggregations; using SQL to query complex groupings and summaries; comparing data to previous inputs to make smart decisions, and identifying readings that exceed historical thresholds. These results can be used to drive real-time dashboards, BI and user interfaces. Traditional database solutions, NoSQL document stores and stream-based software bundles cannot deliver the real-time analysis needed by high-velocity, high-volume Big Data applications.


Make Real-time, Per-event Decisions

Unlike complex stream processing solutions that lack state necessary to support meaningful decision-making, VoltDB’s simple processing model, familiar querying capability, reliability, and scalability offer the performance, rich data interaction, speed and flexibility needed to make decisions. Results are delivered in milliseconds on fast-moving data streams.


Export Processed, Enriched Data to Warehouse/OLAP

Export records of notifications, completed sessions, augmented, enriched records to long term storage or downstream queuing systems – for example Hadoop or Kafka – where your machine learning algorithms, analysts and data scientists refine your strategy and complete the feedback loop.

Combining Fast and Big Data unleashes value. VoltDB’s modern in-memory database architecture is specifically designed to transact against Fast Data, supporting hundreds of thousands of connected devices and users; responding in milliseconds to hundreds of thousands of simultaneous inputs and queries; delivering real-time personalization, real-time security, fraud detection and monitoring, and providing real-time operational analytics.