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Datasheets and Technical Notes

Openet: intelligence industry survey - Big Data 2016

Survey Results of Over 1500 Telecoms Professionals on Trends and Applications of Big Data. Big data is hardly a new term, and has certainly fallen victim to the dreaded hype cycle in the past. This survey intends to understand the audience’s current attitudes to big data implementation, as well as the potential CEM and service benefits of big data done right. Learn how the audience believes big data is best used, and how well it's really being used and supported.

2015 Real-time Data Report

Today’s digital world is dominated by data. It streams into organizations from phones, sensors, financial systems, telecom and IT networks and anywhere a mouse click creates a reaction. This real-time information needs to be captured, analyzed and acted upon in milliseconds to capitalize on the critical insights that can make or break a business. The purpose of the 2015 Real-time Data Report is to determine the state of fast data analysis across the enterprise through the eyes of CIOs, IT managers and developers. Conducted by independent panel research firm Research Now, the survey examined how each of these enterprise roles views real-time data capabilities and requirements. The resulting data revealed a number of discrepancies regarding the definition, analysis and business applications of real-time data.

Comparing Cloud Performance with YCSB

Last year we published YCSB benchmarks that compared IBM SoftLayer with Amazon Web Services. There was so much interest we decided to do it again with more platforms. We reached out to an independent benchmarking enthusiast, Tim Callaghan from ACME Benchmarking to run the tests for us. We compensated him for his time and work, but we took a hands-off approach to the actual benchmarking. Download this datasheet to see more about the results. 

VoltDB Version 5.6 can keep telcos’ business critical applications running

Ovum Telecom Operations and IT Practice Leader, Clare McCarthy, discusses the new VoltDB v5.6. Telcos agree that they should use their data assets more effectively. It is fundamental to their digital transformation and Internet of Things (IoT) strategies, and it is their route to competing more effectively with the disruptive, online players. The additional challenge is that these data volumes are increasing exponentially and require streaming analytics combined with transactions to support taking action. In memory SQL database specialist VoltDB has a solution.

VoltDB for IT Ops Managers

Read this data sheet to learn how VoltDB enables IT operations managers to reduced infrastructure cost, save data from server failures, and meets the latency requirements all while simplifying deployments with ACID properties.

Technical Note: How VoltDB does Transactions

A few years ago (VoltDB version 3.0) we made substantial changes to the transaction management system at the heart of VoltDB. There are several older posts and articles describing the original system but I was surprised to find that we never explained at length how the current transaction system is constructed. This supplement will address questions such as: How do we structure a program to run commands to create, query and update structured data at the highest possible throughput? And how do you run the maximum number of commands in a unit of time against in-memory data?

Technical Note: Announcing incremental MapReduce for VoltDB - explaining materialized views

We are sometimes asked, “When will you add incremental MapReduce to VoltDB?” We did, in fact, implement this feature - in version 1.0 - with our materialized views. At the time, we didn’t have the foresight to call it “Incremental MapReduce,” but rather used the name “Materialized Views.” This supplement provides additional detail about materialized views and will answer questions like: What are VoltDB materialized views? How is data in materialized views accessed? And how do streaming analytics support per-event transactions?

Technical Note: VoltDB Export

This supplement provides additional detail about VoltDB export and answers some common technical questions such as: How is export implemented? And how does export achieve fault tolerance?

VoltDB for Mobile, Telco and Communications Service Providers

Mobile application development is growing to keep pace with consumer demand for new features and apps, especially those that offer increased interaction and personalization. To meet the challenges of creating new, compelling mobile applications, developers need new approaches to manage and extract value from fast streams of structured and unstructured data. Streaming offerings and NoSQL databases offer partial solutions, but fail to deliver the speed, functionality and flexibility of VoltDB. Used by mobile application developers, telco providers and CSPs worldwide, VoltDB enables providers to offer applications that deliver real-time interactions and personalization to improve loyalty, reduce churn and increase average revenue per user (ARPU).

The Secret to Real-Time Customer Personalization in Financial Services

Financial firms need to deliver relevant, personalized customer experiences across a range of devices. This personalization must meet consumer needs, feel responsive, and most importantly react in real-time – which means implementing a scalable solution that can handle streaming data while simultaneously providing real-time context, analytics and decision making.

VoltDB for Amazon AWS

VoltDB makes it simple to run streaming applications in the cloud on Amazon Web Services, using either Amazon’s CloudFormation or your own schema.

VoltDB for IBM SoftLayer

VoltDB enables developers to take advantage of the speed and performance of bare metal servers and the scalability and reliability of cloud when deploying applications to the IBM SoftLayer Cloud.

Big Data Integration

VoltDB is well-known for its fast data ingest capability. Equally important for building real-time pipelining applications is fast export of data. VoltDB offers a broad set of Big Data ecosystem integrations to enable high-speed data export to long-term analytics stores such as HP Vertica and IBM Netezza, as well as Hadoop-based data warehouses. Supported Export connectors include CSV, HDFS/Hadoop, Kafka, RabbitMQ, JDBC, Netezza and Vertica. VoltDB also provides simple-to-use examples and instructions to enable developers to build custom, open-source Export connectors. VoltDB Export enables data to arrive in your analytic store sooner, and allows deep analytics to be leveraged with radically lower latency.

Solving the Fast Data Problem For the Cloud: VoltDB-SoftLayer Benchmark

VoltDB, the industry’s fastest in-memory operational NewSQL database, and the global cloud computing platform from SoftLayer, an IBM company, provides users with the performance of bare metal and the Fast Data processing capabilities required to analyze and make real-time decisions to meet the needs of today’s high-volume, high-velocity businesses.


To be useful, a database needs to be both reliable and available. Durability ensures the persistence of the data in case the database and the server it runs on fail. Availability is the ability to withstand system failures that would normally disrupt the database’s ability to function. It not only preserves the data, but availability also plays a crucial role in ensuring that the database process itself is able to survive.


Durability is one of the four key ACID attributes required to ensure the accurate and reliable operation of a transactional database. Simply put, durability ensures that any transaction that succeeds is committed to the database and made persistent. Even in the event of a power failure or other unexpected occurrence, transactions that have been committed survive permanently. In reverse, any transactions that fail or are interrupted will “roll back” and not affect database integrity.


Without parallelism, the performance of a software system is limited to the speed of a single CPU. In recent years, advances in single-CPU performance have slowed, disproportionate to the increased number of cores-per-machine now packed into commodity servers. Hardware design dictates that, to achieve higher performance, a workload must be parallel.


Scalability is the ability of a system to handle larger workloads by enlarging the system in a straightforward manner. In practice, however, it is often impossible to plan for the scenarios that will most benefit from highly scalable systems. Workloads can drastically expand due to business growth, new application features, and usage patterns. How will your application grow eight years down the line?


VoltDB’s unique and powerful transaction system makes writing simple, fast and reliable real-time analytics and decisioning applications easy. VoltDB supports complex multi-SQL-statement ACID transactions. The transactional system in VoltDB supports serializable isolation, complete multistatement atomicity and roll-back, and strong durability guarantees.

Hadoop Integration

Hadoop is an open-source framework for managing massive amounts of historical data. VoltDB is an in-memory relational database for managing in-the-moment high velocity data. Business applications often require both instantaneous, reliable database execution as well as the archival and analysis of historical data. VoltDB lets you integrate VoltDB and Hadoop to address both needs and get a full picture of your data. This whitepaper explains how.

HP Vertica Database Integration

Many businesses can’t ingest and analyze data as fast as they need to; nor can they make the most of historical data. With VoltDB’s HP Vertica Export Client, organizations can have a database solution that captures not just the front end of Big Data but the back end as well. Merging Vertica’s deep analysis of historical information with VoltDB’s in-the-moment decisioning and analytics in a closed-loop system, businesses can tap vital customer information that makes the difference between profit and loss.

IBM Netezza Database Integration

Data has immense value when it’s created, but if businesses can’t tap it immediately, they’ve lost sight of their customers. Organizations also need to mine historical data to make sense of patterns and trends. That’s why VoltDB’s IBM Netezza Export Client combines historical and in-the-moment data to provide a complete picture to businesses. With a closed-loop system, a single encompassing view of data can empower businesses.

SQL Is Time Tested And Still Flourishing

Structured Query Language (SQL) is far from dead. It continues to help modern databases handle both large-volume analytic workloads and high-performance transaction processing workloads. Facebook, Google and other organizations use SQL to improve interactivity with data, integrate with standard tooling interfaces and deliver on meaningful query optimization. In this article — most of which originally appeared in a Network World feature that debated SQL and NoSQL technologies — VoltDB CTO Ryan Betts lays out why SQL continues to win in the big data market space.

Survey Reveals Big Data Goes to Waste at Most Organizations

In Q1, 2014, VoltDB polled database managers, analysts, administrators and other IT professionals about the databases they use, the results of their Big Data projects, and opinions about Big Data technology advancements. The 2014 Big Data Survey reveals that most organizations cannot access, let alone utilize, the vast majority of the data they collect, and exposes a major Big Data divide: the ability to successfully capture and store huge amounts of data is not translating to improved bottom-line business benefits. What’s to blame? Deficiencies in database performance.

VoltDB In-memory Database Achieves Best-in-class Results, Running in the Cloud, on the YCSB Benchmark

Our dev team recently put VoltDB up against the Yahoo Cloud Serving Benchmark (YCSB) – an industry-standard performance benchmark for cloud databases. And, it went well. Very well. This overview breaks down the benchmark – and VoltDB’s best-in-class performance.