Author
Eric Frenkiel
SingleStore Co-Founder
Company
SingleStore Stands With Our Environment
Yesterday, the world reacted to a move by the U.S. President to withdraw from the Paris Agreement. Almost immediately, voices across America responded with a resounding commitment to maintain alignment with the Paris climate agreement recommendations.
With the energy sector at the center of this conversation, the industry needs more help from technology companies than ever before. Today, the ability to see operations in real time, and have an immediate view on the state of their businesses, is critical in the effective use of energy.
With the support of technology companies, leading energy providers are now able to reduce carbon emissions via smart meters in households, improve the efficiency of environmentally responsible production, and view metrics that help optimize mix fuels such as natural gas, which have some of the lowest carbon emissions of any fossil fuel on a per-unit basis.
There are many people and companies across the world looking to improve our global environmental standing, and we know there is a long way to go. SingleStore salutes you and stands with you to protect our environment.
Eric Frenkiel and Nikita Shamgunov, SingleStore Founders
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Product
SingleStore at Scale and our Series C
We are delighted to announce that SingleStore has raised more than \$36m in a Series C round. The oversubscribed round includes new investors REV Capital, Caffeinated Capital, with full pro rata participation from earlier investors including, Accel (who led our Series B), Khosla Ventures, and Data Collective. When you include the ongoing support of our early investors First Round Capital, In-Q-Tel, IA Ventures, that’s quite the list.
Read the news release ⇒
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Product
Introducing SingleStoreDB Self-Managed 5 Beta
A post from our co-founders Eric Frenkiel, CEO and Nikita Shamgunov, CTO
Today SingleStoreDB Self-Managed 5 Beta is publicly available! SingleStore customers have been able to achieve remarkable results with our database, and we look forward to feedback on this upcoming release from our user community.
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Data Intensity
Predictions 2016: the Impact of Real-Time Data
Prediction 1. The industrial internet moves to real-time data pipelines
The industrial internet knits together big data, machine learning, and machine-to-machine communications to detect patterns and adjust operations in near real time. Soon the industrial internet will expand by definition to include the Internet of Things.
The detection of patterns and insights often comes with a price: time. While the goal of machine learning is to develop models that will prove useful, dealing with large data sets means it can take days, weeks or months to reach meaningful discoveries.
We predict that in the very near future, real-time data streams will transform what is possible across the industrial internet, so users can ask critical questions, adjust a process, or see a pattern in the moment. Entire industries such as energy, pharmaceutical and even agriculture will be dramatically impacted by the ability to analyze real-time and historical data together to make business decisions faster.
Prediction 2. Consumer visibility into business gets granular
The world today moves at a different pace than a generation ago. Applications on handheld devices that move us through our day tell us where to eat, how to get from point A to point B, what is the fastest route, everything that is happening in the world, and even what our friends are buying. Data is driving the course of business – and dramatically impacting the consumer experience.
We predict that in a few short years, consumer visibility into business operations will get more granular. For example, look at the transparency that already exists with companies such as Blue Apron and FedEx. Not only do we know exactly what is on the menu week to week at Blue Apron, we can opt out if it is something we do not like, or adjust the delivery times. And FedEx allows consumers to track the entire journey of a package and sometimes even reroute a package to a new delivery destination. More and more companies will adopt transparency for consumers, and in doing so, will build brand loyalty and satiate growing consumer appetite for on-demand services.
Prediction 3. The cost of doing business declines
Just a few years ago the cost of storage was a board room conversation, where CIOs had to justify the rising cost of IT associated with growing data volumes. For many CIOs, storage was an IT line item that was on track to outpace profitability.
Today, the conversation around data storage has changed. Storage is cheap and highly accessible—any business unit within an organization can tap into the cloud. Access to commodity hardware makes rapidly scaling a business possible.
The cost of doing business will further decline as in-memory technologies set computing on a new course. While companies like Amazon provide access to more than a terabyte of memory for just a few dollars an hour via public or private clouds, other companies have created technology that provides relatively low-cost access to terabytes of non-volatile memory, which developers can use instead of storage. In-memory databases use vast stores of memory close to the compute to rapidly process data. Access to more memory means that programmers will be able to write different types of software—propelling the industry toward what is perhaps a new era of applications built on commodity hardware.
We are already seeing verticalized trends for data analytics and applications that can serve up real-time value across healthcare, manufacturing, and retail. What’s next?
Prediction 4. The crowdsourcing of analytics
The world of artificial intelligence (AI) used to lie solidly in the hands of physicists, scientists and researchers and well beyond mass population. Today, AI has shifted and is empowering people all over the world to participate in the analytics process. Crowdflower, for example – now Appen – blends a human-in-the-loop process alongside data science and machine learning to generate insights. Kaggle, another company crowdsourcing for analytics, has built one of the world’s largest communities of data scientists to solve complex challenges through a competitive approach to data science.
Data analysis will be more pervasive, and new applications that empower the data collection process will be broadly embraced. Consider the power of Waze and INRIX, both in use today to crowdsource traffic congestion. While the requirement is the participation of a social community at large, the upside potential is felt much more broadly. The same data collection process could be applied to many more applications to affect and improve society.
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Product
SingleStoreDB Self-Managed 4: Market and Strategy CEO Q&A
SingleStoreDB Self-Managed 4 represents a leap forward in relational database innovation with new capabilities such as real-time geospatial intelligence and high-throughput connectivity to Apache Spark. It also includes a free forever, unlimited capacity Community Edition, enhancements to the Optimizer for distributed joins, and a new version of the SingleStore Ops management framework.
Start Using SingleStore Community Edition Now
Unlimited scale and capacity. Free forever.
Download Community Edition →
As Big Data abounds, understanding every company and product can be tricky. To make easier, here are a few questions and answers about SingleStore.
The database landscape is big. Where does SingleStore fit?
SingleStore is the leading database for real-time transactions and analytics. That means we’re operational by nature, much more akin to SQL Server, Oracle, or SAP HANA than Hadoop. SingleStore is also:
In-Memory
Providing the utmost performance for today’s demanding workloadsDistributed
Enabling cost-effective, horizontal scale-out on-premises or in the cloudRelational and multi-model
Allowing companies to use in-house SQL tools, applications, and knowledgeWith JSON and Geospatial data formats supportedSoftware
Designed to run on commodity hardware for costs savings
You talk about transactions and analytics. Can you explain in more detail?
To meet real-time demands, companies must be able to capture information across millions to hundreds of millions of sensors or mobile applications. They also want to analyze that data up to the last transaction. So with real-time operations you don’t have the luxury or the pain of ETL. You need to bypass ETL by transacting and analyzing in a single database designed to support these concurrent workloads. It boils down to analytics on changing datasets, today’s critical capability.
SingleStoreDB Self-Managed 4 includes the SingleStore Spark Connector and the SingleStore Loader for HDFS and S3. How should we think about SingleStore with Spark and Hadoop?
SingleStore and Spark work well together as they both have memory-optimized, distributed frameworks. Spark is a processing framework that enables real-time transformation and advanced analytics, but Spark itself does not have a storage or persistence ability. By storing data permanently in SingleStore, customers get an easy way to build operational applications, and the ability to take operational data and ‘round-trip’ it to Spark for advanced analytics.
With Hadoop, customers frequently build simplified Lambda architectures using SingleStore. All data can go directly to HDFS for long term archiving. Simultaneously, data can go directly into SingleStore, bypassing Hadoop for the real-time path. Should historical data be needed for analysis, SingleStore can import that data from HDFS using the SingleStore Loader.
Many folks say not everything needs to be in-memory. How do you respond?
We agree! While in-memory computing remains critical for many applications, the pace of data growth still eclipses memory-only solutions. This is exactly why SingleStore ships with an integrated column-store optimized for disk and flash. Now customers can create tables entirely in-memory, or across a combination of memory and disk and flash. And starting with SingleStoreDB Self-Managed 4, we license the software based on DRAM capacity so the use of disk or flash storage in the column store is unlimited at no additional cost.
We are big believers that customers will see the benefit of placing data in a structured format from the beginning, and the SingleStore column store will let them do that affordably.
You have always focused on SQL. All the while NoSQL has received a lot of discussion. Where is SingleStore in this?
SQL is the lingua franca of the data processing world, having been well adopted over its decades-long history. Companies can build SQL applications quickly, and then immediately use in house analytics tools and practices to derive insights.
Prevailing wisdom used to be that SQL could not scale. That is untrue and companies are now discovering the powerful combination SingleStore delivers of a relational, in-memory, distributed database with speed, scale, and simplicity.
The future is multi-model and SingleStore also includes JSON and Geospatial datatypes to fulfill this promise.
The Community Edition is freely available but not open-source. What strategy is SingleStore pursuing?
Our strategy is to build a scalable software business. This means running on all the platforms customers want to use, including public and private clouds, in the way they want to use them. Community Edition is a way to allow more people to use SingleStore without limitations on time or capacity.
There is a wide spectrum of commercial database offerings. On one extreme there are proprietary hardware / software combinations. Our belief is that proprietary hardware is a down elevator. On the other end of the spectrum there are open-source projects with businesses built around them. But that is essentially selling consulting hours, not software. There are many successful businesses in the middle of the spectrum, such as MySQL’s dual commercial / open-source licensing, and we maintain open-source projects, including SingleStore Loader for Hadoop and S3, a large number of general-purpose Python packages, and the SingleStore Spark Connector.
At SingleStore, we want to offer performance that trumps legacy vendors, deliver it a fraction of the cost, and provide complete deployment choice across hardware, data centers, and clouds. In doing so we hope to help more companies achieve their goals to become real-time enterprises.
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Product
Launching Our Community Edition
We started SingleStore with a vision to enable every company to be a real-time enterprise, and to do that by delivering the leading real-time database for transactions and analytics. Since then, the forces shaping our digital economy have only added wind to our sails. The world is more mobile, interconnected, interactive, and on the cusp of several industry transformations such as the Internet of Things.
Real-time processing is the secret to keeping up, and in-memory solutions are the foundation. Yet existing options have been too expensive or too complex for companies to adopt.
That changes today with the release of SingleStoreDB Self-Managed 4 and our new Community Edition, a free unlimited capacity, unlimited scale offering of SingleStore that includes all transactional and analytical features.
By sharing SingleStore capabilities with the world, for free, we expect many developers and companies will have a chance to explore what is possible with in-memory computing. As the pace of business advances, SingleStore will be there.
Start Using SingleStore Community Edition Now
Unlimited scale and capacity. Free forever.
Download Community Edition →
We hope you enjoy working with our Community Edition. Please feel free to share feedback at our Community Edition Help page.
Eric Frenkiel, CEO and co-founder, SingleStore
Nikita Shamgunov, CTO and co-founder, SingleStore
Community FAQ
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Product
Celebrating SingleStore Availability Two Years In
Today, I couldn’t be more excited to mark the two year anniversary of SingleStore general availability! SingleStore began with a simple idea to build a new database that would give any company the ability to operate in real-time and make their business more data-driven, responsive, and scalable. Since releasing SingleStore, it’s been an amazingly fun journey as the company has grown by leaps and bounds every quarter.
To celebrate our second birthday, I wanted to take a brief moment to reflect on what we’ve been able to accomplish in the two years since releasing SingleStore.
People
SingleStore started in the Y-Combinator winter class of 2011 with just two people – co-founder and CTO Nikita Shamgunov, and myself. Since then, we’ve grown the company to more than 50 people who bring great experience, energy, and passion to the company. We’ve also added database visionaries like Jerry Held and Chris Fry to our executive team to help us see our vision come to fruition.
Customers
We’ve added 40+ enterprise customers over the past 2 years, including top brands like Comcast, Samsung and Shutterstock. It’s been incredibly rewarding to see our customers use SingleStore in ways we never imagined, truly pushing the boundaries of what is possible in Big Data.
Product
Since launching with general availability in 2013, we’ve expanded the SingleStore platform to scale with growing market demand. Major additions to the platform include:
Going beyond memory by including a flash-optimized column store that is closely integrated with the in-memory row store to provide a single database for real-time and historical analyticsWorking with Apache Spark by shipping a bi-directional connector to operationalize Spark models and resultsIncorporating real-time geospatial intelligence to help customers build location-aware applications and analytics
What’s Next?
The most exciting times are still ahead!
Big data has been traditionally thought of as a mechanism for extracting insights from yesterday’s data. We seek to change that way of thinking, empowering businesses to be more responsive by operating with real-time data in the here and now. As demand for real-time and in-memory databases increases, we plan to be there helping customers achieve phenomenal results.
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Company
Welcome Jerry Held as SingleStore Executive Chairman
At SingleStore, we have always respected the challenges the computing industry has tackled in the past. It is no easy feat to build formidable technology companies, and when it happens, we look on with admiration.
It is in that spirit that we are thrilled to welcome Jerry Held as Executive Chairman of SingleStore. Jerry’s experience in technology across computing and database technology is unparalleled. A consummate technology innovator and entrepreneur, he has helped create new database technologies and new companies, beginning with pioneering work to build the INGRES database during his time at U.C. Berkeley, and then Tandem, where he built it from a startup to reaching over $2 billion in annual revenues. He ran Oracle’s server products division during a growth period from $1.5 billion to \$6 billion in annual revenues. He served as “CEO-in-residence” at Kleiner Perkins Caufield & Byers. He served as lead director of Business Objects until its sale to SAP, and was executive chairman of Vertica until its sale to HP. Today he serves as the chairman of Tamr and on the boards of Informatica, NetApp, Kalio and Copia Global.
SingleStore Welcomes Database Visionary Jerry Held as Executive Chairman – Click to Tweet
In short, Jerry is an expert in high-growth technology companies and knows the opportunities they create. He has seen the full picture and enjoys sharing his expertise.
SingleStore began with a simple idea to build a new database that would change the way people think about business: every company should be a real-time company, using SingleStore to make their businesses more data-driven, responsive, and scalable.
To achieve our objectives, we have surrounded ourselves with the best and brightest in the industry, in turn delivering our customers easy access to database innovation. Jerry epitomizes the talent and experience we continue to seek at SingleStore.
As we continue the expansion of our business and world-class product, we look forward to Jerry’s participation in reshaping the real-time database landscape. Welcome, Jerry!
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Product
SingleStoreDB Self-Managed 2.5 Ships Today with JSON Datatype, Online Alter Table, and More
We are excited to announce that SingleStoreDB Self-Managed 2.5 is now available for download. Of the many new features and performance improvements, one of the most exciting is support for JSON analytics. With native support for the JSON datatype, SingleStore delivers a consolidated view across structured and semi-structured data in real-time.
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Company
Growing Our Executive Team
I’m excited to announce today that SingleStore has expanded its executive team with the hiring of Carl Wright as EVP of Worldwide Sales. Carl is exceptional both as a technologist and as a sales leader. We are delighted he has joined SingleStore to help us capture all the demand we’re seeing since we announced the release of our distributed memory-centric real-time analytics platform last month. Carl is already active in the field with customers and prospects while building a top-notch team for SingleStore.
Carl joins us from Coraid, where he increased their revenue 12x in three years and brought on 1,500 new customers. He’s also held executive positions at Kidaro, acquired by Microsoft, and Decru, acquired by NetApp. Before this, he was Chief Information Security Officer for the U.S. Marine Corp, where he was responsible for a network that supported 120,000 users worldwide, so he’ll ensure excellent technical depth on our sales team. You can read more in our press release.
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Product
SingleStore ships 2.0. Scales in-memory database across hundreds of nodes, thousands of cores.
When we started SingleStore a little over two years ago, our goal was to deliver the fastest OLTP database ever. Inspired by the scale and architectures we saw at Facebook, we hoped to help every enterprise leverage in-memory technologies similar to those that leading web companies use.
As we worked with our early customers, we saw that an in-memory solution could provide the greatest value by enabling users to analyze real-time and recent historical data together. Customers like Zynga and Morgan Stanley not only wanted to quickly commit transactions to the database, they also wanted instant answers to questions about how their real-time data compared to historical data. This inspired us to build something new – a solution that supports highly concurrent transactional and analytical workloads at Big Data scale.
That brings us to today. We’re proud to announce that SingleStore’s real-time analytics platform is available for download. This is the first generally available version of SingleStore that scales horizontally on commodity hardware. It provides the blazing fast performance for which SingleStore is known, and now does it at Big Data scale. Customers have deployed SingleStore across hundreds of nodes and dozens of terabytes of data, and we’ve tested at even greater volumes and velocities. (Check out our calculator to get an idea of the number of reads and writes you can perform depending on the size of your cluster.)
This is also the first version to include SingleStore Watch, a visual web-based interface for monitoring and managing your cluster. We expect this to be the beginning of our foray into real-time visualizations as many of our customers look to operationalize their analytics.
Deploying a database can be difficult, so we’ve made it as simple as possible. Download SingleStore for free on our site and take it for a spin. You’ll definitely be impressed by the performance, but you’ll also be impressed by what’s missing:
Batched loading – Don’t wait until the middle of the night to refresh your reports.Complicated programming languages (and a limited talent pool) – Use SQL for real-time analytics.An expensive, proprietary box (and a plan to rip and replace it in a few years) – Scale incrementally on commodity hardware.A lengthy implementation cycle – Launch your first SingleStore instance in minutes in the cloud.
We’re proud of the progress our engineering team has made building out an enterprise-grade software solution. Stay tuned to this blog to learn more about the real-time analytics challenges we are helping customers conquer. More to come.
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