TECHNICAL OVERVIEW
VoltDB for Financial Services Technical Overview
Financial services organizations have multiple masters: regulators, investors, customers, and internal business users. All create, monitor, and require access to vast amounts of data, generated and viewed on myriad devices and platforms. This data must be immediately accessible, always-correct, and stored for varying periods of time, depending on local, country and global regulations. For finserv companies, data is currency.
Yet aging, largely proprietary infrastructures lack the flexibility and scale required to respond to today’s highly-net- worked, regulated, data-intensive financial applications. Fraud, a global, Internet-scale business, is an evolving threat. Financial services institutions must manage vast streams of data in real time while storing troves of transaction and profile data, with audit trails, to maintain relevance in a highly-regulated, competitive marketplace. Traditionally, these institutions relied on legacy relational database management systems; in the past decade, the rise of NoSQL has changed the options for enterprise architects and developers in financial services. Let’s look at a range of data management options, and describe the technical benefits of VoltDB, an in-memory, NewSQL on-line transaction processing (OLTP) database.
The operational complexity of many databases, from legacy RDBMSs to open source options, can be daunting. Full-time DBA support isn’t an option for many small-medium companies, and can represent a significant seven-figure sum for larger ones. Architectural complexity, scale out vs. scale up issues, HA and cross-datacenter replication, data consistency, cloud-readiness, capacity for virtualization, even old-school locking and latching present issues more familiar to a distributed systems expert than to an app developer or DBA. More importantly, operational complexity inevitably bubbles up to affect end users.
Many NoSQL offerings, which offer a more flexible approach to scale out, flexible schema and data types, fail on support for scalable transaction support when working with shared, finite resources: credit balances or trade verification, risk management, fraud detection and management, and customer interaction and personalization, to name a few use cases.
Financial services organizations build value on transactional applications:
• Fraud and risk management — Preventing credit card fraud requires banks to protect their customers and contain losses by monitoring each card swipe to detect unusual or fraudulent activity, and make an immediate decision to allow a purchase to go through — or to block it as fraudulent.
• Trade reconciliation — Proprietary workflows for processing trades, where managing high volumes of financial transactions require the ability to monitor, record, log and index transactions to comply with regulations and maintain an accurate view of transaction history. Two common problems are requesting history replay and state recovery, both of which are necessary to maintain accurate records and avoid regulatory fines. TECHNICAL OVERVIEW
• Bid & offer management — Brokers must route trade orders to the market with the best price, and by law must guarantee customers the best available price, to comply with the National Best Bid and Offer (NBBO) regulation. NBBO is defined as the lowest available ask price and highest available bid price across participating markets for a given security.
• Regulatory compliance — Regulations such as Dodd-Frank, Sarbanes-Oxley, Basel III and the pending MiFID II require institutions to prove all databases and replicas are the same, with audited consistency across different data sources. In addition, institutions must comply with the SEC’s National Best Bid & Offer regulation.
Financial services applications directly affect an institution’s revenue stream. Institutions require tight, predictable latencies for physical transactions, such as approval of credit card swipes — in the range of sub 20ms — so performance and scalability are non-negotiable requirements. VoltDB is the best solution available for ingesting, analyzing and acting on the massive volumes of real-time data streaming from trading, fraud detection and bid & offer management systems. It combines accuracy, scalability and manageable TCO, even for cutting edge scenarios such as managing trading operations, detecting credit card fraud in real-time, and managing quality of service for many millions of users based in multiple data centers simultaneously.
VoltDB Basics
VoltDB is an in-memory, SQL, cloud-ready operational database for modern applications that require the ability to manage data at unprecedented scale and volume, with 100% accuracy. VoltDB rapidly imports, operates on, and then exports vast amounts of data at lightning speed. Its robust architecture combines the best of traditional transactional databases with the speed and scalability of newer entrants.
Unlike OLTP, Big Data, and NoSQL offerings that force users to compromise, only VoltDB supports all three modern financial services application data requirements:
1. Millions — VoltDB processes relentless volumes of data from users, devices and sources.
2. Milliseconds — VoltDB ingests, analyzes, and acts on data in milliseconds, with predictable low latency.
3. 100% — Data managed by VoltDB is always accurate, all the time, for all decisions.
Financial Services organizations use VoltDB to modernize revenue and business-critical applications, including:
• Fraud and risk management
• Trade reconciliation
• SLA management
• Regulatory compliance
VoltDB was founded by a team of world-class database experts, including Dr. Michael Stonebraker.
2 VOLTDB FOR FINANCIAL SERVICES TECHNICAL OVERVIEW TECHNICAL OVERVIEW
Why VoltDB?
VoltDB is adopted in Financial Services because it’s well suited to both the current needs of vendors and the challenges they anticipate in future. VoltDB has been written from scratch to work in a 21st century RAM-centric environment and to meet the demanding requirements of Financial Services institutions.
VoltDB makes instantaneous decision-making possible by combining the best elements of modern and traditional database technology:
• The speed and scalability of the best distributed data architectures, combined with the ACID transactionality of traditional RDBMSs — without the licensing hassles.
• The consistency and reliability financial institutions need, deployed with a more streamlined, cloud-ready, highly-available, simple architecture.
• Active-active, multi-version cross-datacenter replication.
• The tools and languages developers already know.
Technical Details
VoltDB was designed by Dr. Michael Stonebraker to address the shortcomings of traditional online transaction processing ( OLTP) systems. With VoltDB, Stonebraker and his team were able to eliminate performance issues such as latching and locking, buffer management, and transaction management. For a more detailed look at the decisions behind VoltDB’s architecture, read the Technical Overview here.
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