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Row-Level Security for SingleStoreDB
Blog

Row-Level Security for SingleStoreDB

Having fine-grained access to data in the database is critical. As we think about data security in databases, SingleStoreDB supports fine grained access control that can help customers to set the right level of access to the data.This is achieved through a fully functional Role based Access Control (RBAC) mechanism  which ensures that only the right level of privileges are given to each user to access the right database objects. However, how can users bring in additional security to data within a table itself — thereby ensuring more granularity of control to users?One key capability SingleStoreDB supports is Row-Level Security (RLS), a feature that’s been included since  SingleStoreDB 7.3. This provides the ability to ensure that the specific users/groups are able to see only specific segments of the tables based on the roles they assume.  By default, any user/group who has access privilege to a table essentially has access to all rows in it based on the SQL privilege system and all rows are available for manipulation.With Row-Level Security we can prevent the exact rows that users can manipulate. It is a very strong capability to implement data security — especially for applications where data from multiple tenants are stored in a common table definition.Use CasesHere are some examples where Row-Level Security is very critical and can be used:A sales representative should only see the rows which are related to customers that they are working withIsolating data across different users’ segments in a multi-tenant application. This could be due to multiple customers' data being stored in a single table, but isolated from each other from application perspectiveRow-Level Security is a role-based access control mechanism for granular level objects within a table. It is  flexible, centralized and scalable. The security is based on access permissions defined for each role-row pair in the table as the administrator sets it up. Based on the role-row pairing criteria, the right level of access to the data is maintained.Benefits(RLS) benefits an organization by balancing security and governance at scale using a RBAC model. The scalable aspect of the model refers to the fact that it can be dynamically changed at any time to meet the corporate policy of the organization.Additional benefits include:Ease of useChange management— we can easily change the roles and users tied to that role, without having to reapply the change the roles accessing rows of the tablesNow that we know what Row-Level Security (RLS) is and the benefits of using it, let’s see the functionality in action. In this example we have two scenarios:A global user is the owner of and able to access all sales data, but we want to restrict regional sales people to only view sales data pertaining to their countryWe have two additional salespeople — one in  Canada and one in the U.S. The Canadian user shouldn't access U.S. sales data, and the U.S user shouldn't access Canada sales data.SchemaWe will first  create a database, a table that has an access_roles column and then insert the data:DROP DATABASE if EXISTS row_level_security;CREATE DATABASE row_level_security;USE row_level_security;DROP TABLE IF EXISTS sales_data;CREATE TABLE sales_data ( tx_date DATETIME, country VARCHAR(20), amt REAL, access_roles VARBINARY(50) DEFAULT "," NOT NULL);INSERT INTO sales_data VALUES (now(),'US', 100.11, ',us_sales_role,');INSERT INTO sales_data VALUES (now(),'CAN',200.22,',canada_sales_role,');SELECT * FROM sales_data;See the screenshot here to see it in action:
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Achieving Successful Operation of AI & ML Driven Applications
eBook

Achieving Successful Operation of AI & ML Driven Applications

This ebook helps you understand how to successfully deliver model-driven applications with the speed and scale needed for modern business. By applying models to real-time event streams and historical data, a broader set of signals can be identified and detected for providing improved situational awareness and better business outcomes.
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Dell Transforms PRISM Inventory System to Run at the Speed of Business
Case Study

Dell Transforms PRISM Inventory System to Run at the Speed of Business

“We considered MariaDB and NoSQL databases, as well as Oracle Database in-memory. What we wanted was a relational database that had the speed of NoSQL. We chose SingleStore.”
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20x to 100x Faster Analytics Through Data Warehouse Augmentation
eBook

20x to 100x Faster Analytics Through Data Warehouse Augmentation

In this eBook, you will learn how you can dramatically increase data warehouse performance and accelerate time-to-insights by enhancing your data ingestion capabilities, increasing query speed, and providing exceptional concurrency for all types of analytic activities—often at only one-third the cost of running legacy infrastructure.
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Turbocharge Your SaaS Applications and APIs With SingleStore
Infographic

Turbocharge Your SaaS Applications and APIs With SingleStore

Boost performance with the one database for all data-intensive applications
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Cloud-Native Transactions and Analytics in SingleStore
Research Paper

Cloud-Native Transactions and Analytics in SingleStore

The last decade as seen an incredible rise in specialized database systems. Since its inception, SingleStoreDB has emerged as a revolutionary database designed with the versatility to run both operational and analytical workloads for some of the world's largest financial, telecom, high-tech and energy companies.
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Where Should Top Coders Work?
Blog

Where Should Top Coders Work?

My career as a software engineer really began when I won a medal at the ACM ICPC programming contest in 2001. To place in the tournament, I had spent 24 hours traveling from Russia to Vancouver and back, just to spend 5 hours on the actual competition.The rules are simple: you have 5 hours to solve up to 12 problems. For each problem you need to implement a small program in Java or C++ and send it to the jury. They compile it and run it through an extremely intensive set of tests. Only if it passes every test will the jury count your submission.Even though it only marked the beginning of my career, it had taken 4 years of intense preparation to place at the tournament – 4 years of training, learning to think fast, practicing on weekends, and other sorts of mental gymnastics. ACM was a good school for me. Iloved it, but I wasn’t alone.Is it really hard to become a Top Coder?Becoming an ACP ICPC medalist in 2011 is about 20 times harder than it was in 2001. People who can do it now are coding machines and algorithm junkies. They practice every day on TopCoder, Google Code Jam, and Code Force to stay sharp. They memorize whole books filled with algorithms and equations in case they need a tool to solve a problem quicker than their opponent. It should be no surprise that this programming subculture has caught the attention of many great companies.So where do programming contest winners go and work? It used to be Microsoft (where I started my career), then Google. Now it’s Facebook. These companies know how valuable top coders are. Microsoft, Google and Facebook wouldn’t be where they are without exceptional engineers.How do Top Coders fare after graduation?They fare very well and tend to build their careers at big companies. Many are attracted to the high salary right out of school. However, according to topcoder.com, many ultimately find work at large companies to be tedious and less challenging than the mental jujitsu of programming contests.Large teams have the luxury of compartmentalizing a problem to reduce complexity. This creates an unfortunate side effect: these smaller problems just aren’t that interesting.In addition, many ICPC champions soon miss the dynamic of small teams, the kind they experienced while training and competing during university.As it so happens, there is a time in a company’s history when it’s perfect for a top coder to join – when the company’s just getting started.Why do some Top Coders found/join an early-stage startup?For the challenge, of course.Just take a look at these real-life examples:Adam D’Angelo was a finalist in the international Topcoder Collegiate Challenge in 2005. Later he was VP and CTO of Facebook and then left to found Quora.Nikolai Durov is Employee #1 at the biggest Russian social network vkontakte. It beats Facebook on the Russian market. He could’ve gone to Google or stayed in academia, but he made a small bet that had lots of upside.One of my team members Leonid Volkov went to an early stage company and built the “TurboTax of Russia”. He enjoyed an incredibly successful exit, and he’s since gone into politics.Prasanna Sankaranarayanan is the founder of LikeALittle and was the highest ranked Top Coder in India. It took him one year at Microsoft to realize that the perfect job for a Top Coder is at an early stage startup.Small startups offer Top Coders lots of responsibility and with it the trust and autonomy to solve tough problems.Top Coders at SingleStoreToday, SingleStore has four Top Coders. I won a bronze medal in ACM ICPC in 2001, and Alex Skidanov was a Top Coder #13 in 2008 and ACM ICPC #3 Champion. A Top Coder would feel right at home at SingleStore. Here, we work on hard algorithmic and systems-level problems, distributed systems, and cloud infrastructure. We also now have Top Coders who ranked #4 and #8 in algorithms. Sometimes it’s scary to leave a big corporation, but the truth is that apart from fun, market pay, and the potential of a huge upside, a good early stage startup gives the kind of experience that makes a Top Coder extremely relevant in today’s tech industry.If you’d like to learn more, shoot us an email at topcoders@singlestore.com.
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HumAIn Podcast: Data Science and Breakthrough Innovation with Oliver Schabenberger
Blog

HumAIn Podcast: Data Science and Breakthrough Innovation with Oliver Schabenberger

Oliver Schabenberger, Chief Innovation Officer at SingleStore sat down with David Yakobovitch, publisher of the HumAin Podcast and Head of Education and Training at Singlestore to discuss the role data science plays in making breakthrough innovation possible. Listen to the full episode, or read the transcript below.
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Spin Up a SingleStore Cluster on Docker Desktop in 10 Minutes
Blog

Spin Up a SingleStore Cluster on Docker Desktop in 10 Minutes

Even though SingleStore is a distributed system, you can run a minimal version of SingleStore on your laptop in Docker. We tell you how in this blog post. The combination of free use of the software, and being able to run SingleStore on your laptop, can be extremely convenient for demos, software testing, developer productivity, and general fooling around. In this post we’ll quickly build a single-instance SingleStore cluster running on Docker Desktop, on a laptop computer, for free. You’ll need a machine with at least 8GB RAM and four CPUs. This is ideal for quickly provisioning a system to understand the capabilities of the SQL engine. Everything we build today will be running on your machine, and with the magic of Docker containers, we’ll not need to install or configure much of SingleStore to get it running.
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SingleStore: My First *Real* Startup Experience
Blog

SingleStore: My First *Real* Startup Experience

This is reposted from Momchil Tomov’s blog. Momchil was part of the first summer batch of SingleStore Interns.After seemingly stumbling into their office by accident, getting interviewed on a lark, and receiving an offer as my Christmas gift, I kept an open mind for what to expect from SingleStore. The one-year-old YC alum was set to build the world’s fastest database, leaving competitors like MySQL and MongoDB in the dust. Very ambitious indeed.From day one, I was thrown in the fire pit. Someone had to finish the Workload Simulator, an important developer tool, before the launch. Everyone was super busy fixing bugs and polishing the product, so I had to do a quick Javascript/Flask/Python crash course and jump on it. After eight long nights, a thousand lines of code, and a huge amount of support from Ankur, my mentor, the Workload Simulator was finished to coincide with launch.I spent the next month working on code generation: writing code that compiles SQL to C++, the core strength of SingleStore. Once I got acquainted with the codebase, Ankur decided to step up my game with data compression. I had to find a way to compress 10 TB of random strings down to at most 5 TB without compromising the speed of the transactions, and I had two weeks to do so. After some research, experimentation, and lots of dumb luck, I managed to bring it down to 2 TB. It required all the SingleStore knowledge I had obtained thus far, including things I learned during my interview.Just as I finished the first prototype, I joined the team working on sharding. Sharding is what enables SingleStore to get distributed across multiple machines, an important feature of every scalable database and also an important feature for our biggest clients. I was onboarded on Sunday, began work on Monday, and shipped my first code review on Tuesday. One of the dev leads, Ankur, gauged my progress, and kept assigning me more and more sharding tasks, slowly walking me through the implementation of Distributed SingleStore. Just as a father silently lets go of the back seat of his kid’s bicycle, he slowly backed away and moved on to testing and bug fixing. Before realizing it, I found myself working on the team with no safety wheels, full speed ahead, pushing the forefront of SingleStore. I was no longer an intern. I was a full-time SingleStore engineer.They say Princetonians work hard and play really really hard. If that’s true, then SingleStore felt even more like home. From the extraordinarily delicious meals prepared by our in-house chef Daniel, to the post-launch Las Vegas Celebration Trip, to the relaxing Saturdays on Vasili’s boat underneath the Golden Gate, the SingleStore team knows how to have a good time. As SingleStore is growing, I sincerely hope they maintain their great culture of ridiculous engineering and chill free time. I had an amazing summer many thanks to the incredible people at 380 10th Street. I wish Eric, Nikita, Marko, Vasili, Alex, Masha, Nika, Pieguy, Adam, Ankur, Daniel, et al. all the best and hope they build a company 300x better than the rest!Go SingleStore!
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ChatGPT Dev Day & Happy Hour @ AWS London
Webinar

ChatGPT Dev Day & Happy Hour @ AWS London

Check out our ChatGPT Dev Day & Happy Hour @ AWS London! Learn to work with vector databases, prototype GPT apps, and build mini Generative AI apps with Langchain, AutoGPT, Hugging Face & OpenAI.
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Eliminate Database Sprawl
Infographic
Eliminate Database Sprawl
Reduce Costs and Complexity by Unifying all Your Data into One Modern Cloud Database
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SingleStore Helps Siemens Make Smart Decisions in Real Time
Case Study
SingleStore Helps Siemens Make Smart Decisions in Real Time
Siemens now supports 100,000 concurrent users, helping even the largest global organizations transform complexity into operational excellence.
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Query Optimization Time: The New Bottleneck in Real- time Analytics
Research Paper
Query Optimization Time: The New Bottleneck in Real- time Analytics
In the recent past, in-memory distributed database management systems have become increasingly popular to manage and query huge amounts of data. For an in-memory distributed database like MemSQL, it is imperative that the analytical queries run fast.
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Imperva: Unifying and Modernizing Databases with SingleStore and Twingo
Video
Imperva: Unifying and Modernizing Databases with SingleStore and Twingo
Imperva is a nine-time Leader in the Gartner® Magic Quadrant™ for Web Application and API Protection (WAAP). Learn how it has built a cybersecurity one-stop shop with SingleStore and Twingo.
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Business Leader Breakout Session
Product Release
Business Leader Breakout Session
What makes an application data intensive? How do business drive real-time capabilities not just for analytics, but applications? The [r]evolution 2022 ITDM and business leader breakout session dives into these tough, but important, questions — and we brought a few guests along to help answer them. You'll hear from leaders at IBM, Siemens, Digital Asset Research and more.
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10 Apps Syncing to the Pulse of Your Life
Blog
10 Apps Syncing to the Pulse of Your Life
We live in a burgeoning on-demand economy. Services have transcended the physical establishments of restaurants, banks, and shopping malls with universal facilitation by mobile applications. Hordes and hordes of application choices.  And we depend on them daily. It begins with the drop of a pin. Uber arrives at your door several minutes later and off you go to the gym. Now it’s Fitbit’s turn to perform, as it tracks heart rate and chimes gently to let you know workout goals for the day have been completed. Another Uber ride later, you’re at the office, where packages are shipped with the help of Shyp, friends are reimbursed for weekend expenses with Venmo, and the witty line from your boss during this morning’s meeting has made its way into the Twittersphere. And those are only a few examples in a broad sea of apps. Today’s mantra: “There’s an app for that” The global community embraces apps for everything from gaming and shopping, to banking and transportation. Check out the slideshow below, 10 Apps Syncing to the Pulse of Your Life, to see some of the compelling statistics revealing how seamless a part of our lives these apps have become.
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Row-Level Security for SingleStoreDB
Blog
Row-Level Security for SingleStoreDB
Having fine-grained access to data in the database is critical. As we think about data security in databases, SingleStoreDB supports fine grained access control that can help customers to set the right level of access to the data.This is achieved through a fully functional Role based Access Control (RBAC) mechanism  which ensures that only the right level of privileges are given to each user to access the right database objects. However, how can users bring in additional security to data within a table itself — thereby ensuring more granularity of control to users?One key capability SingleStoreDB supports is Row-Level Security (RLS), a feature that’s been included since  SingleStoreDB 7.3. This provides the ability to ensure that the specific users/groups are able to see only specific segments of the tables based on the roles they assume.  By default, any user/group who has access privilege to a table essentially has access to all rows in it based on the SQL privilege system and all rows are available for manipulation.With Row-Level Security we can prevent the exact rows that users can manipulate. It is a very strong capability to implement data security — especially for applications where data from multiple tenants are stored in a common table definition.Use CasesHere are some examples where Row-Level Security is very critical and can be used:A sales representative should only see the rows which are related to customers that they are working withIsolating data across different users’ segments in a multi-tenant application. This could be due to multiple customers' data being stored in a single table, but isolated from each other from application perspectiveRow-Level Security is a role-based access control mechanism for granular level objects within a table. It is  flexible, centralized and scalable. The security is based on access permissions defined for each role-row pair in the table as the administrator sets it up. Based on the role-row pairing criteria, the right level of access to the data is maintained.Benefits(RLS) benefits an organization by balancing security and governance at scale using a RBAC model. The scalable aspect of the model refers to the fact that it can be dynamically changed at any time to meet the corporate policy of the organization.Additional benefits include:Ease of useChange management— we can easily change the roles and users tied to that role, without having to reapply the change the roles accessing rows of the tablesNow that we know what Row-Level Security (RLS) is and the benefits of using it, let’s see the functionality in action. In this example we have two scenarios:A global user is the owner of and able to access all sales data, but we want to restrict regional sales people to only view sales data pertaining to their countryWe have two additional salespeople — one in  Canada and one in the U.S. The Canadian user shouldn't access U.S. sales data, and the U.S user shouldn't access Canada sales data.SchemaWe will first  create a database, a table that has an access_roles column and then insert the data:DROP DATABASE if EXISTS row_level_security;CREATE DATABASE row_level_security;USE row_level_security;DROP TABLE IF EXISTS sales_data;CREATE TABLE sales_data ( tx_date DATETIME, country VARCHAR(20), amt REAL, access_roles VARBINARY(50) DEFAULT "," NOT NULL);INSERT INTO sales_data VALUES (now(),'US', 100.11, ',us_sales_role,');INSERT INTO sales_data VALUES (now(),'CAN',200.22,',canada_sales_role,');SELECT * FROM sales_data;See the screenshot here to see it in action:
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