VoltDB is a relational SQL database that combines context, real-time analytics, and strong consistency to provide the most sophisticated decisions in milliseconds.
VoltDB powers applications that require real-time intelligent decisions on stream- ing data for a connected world, without compromising on ACID requirements. No other database can fuel applications that require a combination of speed, scale, volume and accuracy.
Here's the core functionality that makes VoltDB fast, easy to use, and secure:
VoltDB was designed to deliver real-time query responses on streaming data. A TPC-C / on-line transaction processing benchmark study conducted by Samsung & VoltDB was able to deliver 5 Million new order transactions per minute.
VoltDB can deploy complex Machine Leaning models in-database for real-time analytics in production at unmatched speed and scale.
One unified data platform for files, database and streaming applications.
Proven Production Readiness Get the benefits of both open source and our architectural enhancements for enterprise-grade dependability, security, and multi-tenancy.
Consistent High Performance Eliminates downtime and performance bottlenecks, while ensuring business continuity.
Legacy database technology was focused on analyzing historical data to gain a rear-view understanding of business performance. While it is important to analyze where the business is coming from, in order to gain the competitive advantage and differentiate your application it is critical to utilize deep learning and take action in-event; with the end goal of driving desirable business outcomes.
Building a robust predictive analytics model is only half the battle. Utilizing the model in production for real-time decision making is the key element of Machine Learning, this however is easier said than done. Most organizations have historical data stored in multiple places such as a data warehouse, data lake, ERP system, and more. In addition to existing data, a high volume of data is constantly streaming in from multiple sources at a very high velocity. In a production environment, the Machine Learning model needs to continually ingest, train on historical data and operationalize in real-time at very low latency.
Here's a reference architecture of a VoltDB with MapR system is used in production to operationalize Machine Learning models in real-time:
Transactional data streams into a VoltDB cluster from a message bus for real-time transactional analytics. VoltDB is utilized as an ACID complaint in-memory operational database; it periodically persists data to MapR for storage and historical analytics. Historical data sets are used to build and train a Machine Learning model in tools such as Apache Spark. The PMML files from Apache Spark are deployed into a VoltDB Java stored procedure. As new data streams into VoltDB it is analyzed in real-time by invoking the stored procedure / Machine Leaning model to make and execute real-time decisions. The VoltDB Exporter can feed the decisions back to MapR and/or to an external source such as a Point of Sale system to either approve/deny a financial transaction.
VoltDB serves as a real-time application database used in conjunction with the MapR-FS file system and analytics results derived from Big Data in applications including: real-time scoring, policy enforcement, and customer interaction. VoltDB provides the ability to ingest data as fast as it arrives; perform real-time analytics in-memory; make automated decisions in real-time; and continuously export, processed data into MapR-FS.
VoltDB also supports Kubernetes; enabling continuous and frequent deployment of real-time apps in the public, private, and hybrid clouds. VoltDB's Kubernetes module enables organizations to automate the deployment of VoltDB clusters, reducing application development timescales down from months to minutes.
MapR overcomes the limitations of Hadoop with an underlying data platform that scales to meet any workload with extreme performance. MapR provides a fully read-write file system that brings unprecedented dependability, ease-of-use, and world-record speed to Hadoop, NoSQL, database and streaming applications in one big data platform. The MapR Data Platform provides unique capabilities for management, data protection, and business continuity.
A MapR Typical Pipeline with VoltDB is shown below:
VoltDB provides support for high-velocity export of processed data via a built-in, transactional extract feature. VoltDB Export feeds processed data to MapR-FS. Application developers can automate the export process by specifying tables in the schema as sources for export. At runtime, any data written to the specified tables is sent to an export connector, whose job it is to move these tuples to the export target safely and with the lowest possible latency. VoltDB provides connectors for export to files (CSV); via WebHDFS to Hadoop; via data serialization and exchange services such as Avro; and for export to other relational databases via JDBC.
MapR Technologies, Inc., provider of the industry's leading data platform for AI and Analytics, enables enterprises to inject analytics into their business processes to increase revenue, reduce costs, and mitigate risks. MapR addresses the data complexities of high-scale and mission critical distributed processing from the cloud to the edge, IoT analytics, and containers persistence.
VoltDB powers applications that require real-time intelligent decisions on streaming data for a connected world, without compromising on ACID requirements. No other database can fuel applications that require a combination of speed, scale, volume and accuracy.
Try out either the free VoltDB open source Community Edition, VoltDB on AWS, or the VoltDB Enterprise Edition here: www.voltdb.com/try-voltdb/
Get the MapR Sandbox for free. Try out our fully functional Hadoop cluster running on a virtual machine. Visit mapr.com/sandbox/