At Cazton, we provide first class Blockchain consulting and Blockchain training services. Our team of Blockchain Specialists, Blockchain Consultants and Developers can assess your business requirements and consult if blockchain suits as the perfect solution. While our experts help you develop the correct blockchain solution, we also help you adapt and integrate blockchain into your existing network, develop and deploy smart contracts, token creation, ICO auditing, perform smart contract audits, public and private blockchain creation, wallet security solutions, wallet integration, and much more. Contact us now to learn more about our cloud services.
Cazton offers first class Blockchain consulting and Blockchain training services where we assess your business requirements and consult if blockchain suits as the perfect solution. Our Blockchain Specialists, Blockchain Consultants and Developers can help you adapt and integrate blockchain, develop and deploy smart contracts, token creation, ICO auditing, perform smart contract audits, public and private blockchain creation, wallet security solutions, wallet integration, and much more.
Our CEO, Chander Dhall, became fascinated with machine learning over a decade ago. Having a masters in computer science, he has always kept up with academia even though the company primarily works on projects for mid and large size Fortune 500 corporations. Having been awarded by both Microsoft (Microsoft Most Valuable Professional for close to a decade) and Google (Google Developer Expert), he has been fortunate to interact and share knowledge with the ones who create these technologies.
Our CEO, Chander Dhall, became fascinated with machine learning over a decade ago. Having a masters in computer science, he has always kept up with academia even though the company primarily works on projects for mid and large size Fortune 500 corporations.
Spark is an open-source, lightning fast, cluster computing framework that provides a fast and powerful engine for large-scale data (Big Data) processing. It runs programs up to 100x faster in-memory and 10x faster on disk when compared to Hadoop’s MapReduce system. The reason for Spark’s success is its ability to process data in-memory (using RAM) that allows faster retrieval of data as compared to querying and searching on disk.
Over the years, Spark has seen great acceptance in the technology industry. When it comes to large scale data processing or Big Data analytics, Spark has gained a lot of attention due to its lightning fast processing speed, batch and stream data processing, support for a variety of data sources and easy to integrate with applications written in C#, Java, Scala, Python and R.
With every passing second, the amount of data shared and transferred between humans is unimaginable. To manage, analyze, make predictions and decisions using that data is a daunting task. With data being a critical asset, companies today strive to understand the latest market trends, customer preferences and other requirements, thus making understanding large amount of data imperative.
Cazton has been a pioneer in Big Data Consulting and one popular technology that powers Big Data is Apache™ Hadoop. Hadoop is a highly scalable open-source framework written in Java, which allows processing and storage of terabytes or even petabytes of structured and unstructured complex data (Big Data) across clusters of computers. Its unique storage mechanism over distributed file system (HDFS) maps data wherever it is located on a cluster. The speciality of Hadoop is that it can scale from one server to hundreds of servers and can still perform well. It is fast, flexible and cost-effective as compared to traditional storage systems.
Imagine a process which converts unstructured, unreadable pieces of information into something that is extremely valuable for your organization? information that gives you insights about your business, your products, customers and their preferences. Now imagine getting those insights in real time! We are talking about a process that gives you instant information about an active transaction. Such information is always valuable, isn't it
Do you face problems while scaling data in memory? Are you facing slow processing times? Do you want scalability and as well as atomic transactions? Do your machine learning models require a lot of time for training and production?
Did you know there are more than 1500 companies using Cassandra to handle huge volumes of data? Did you know that some of the largest production deployments include Apple's, with over 75,000 nodes storing over 10 PB of data, Netflix (2,500 nodes, 420 TB, over 1 trillion requests per day), Chinese search engine Easou (270 nodes, 300 TB, over 800 million requests per day), and eBay (over 100 nodes, 250 TB)?
Have you ever encountered SQL Server code with more than 50 joins in a query? Have you ever seen code that retrieves millions of records SQL Server to the Web Server just to return one record to the User Interface? If yes, that's great. This is our daily job.
Did you know PostGres is the fastest growing relational database that is not only free and open source, but rivals the performance of paid RDBMS databases like Oracle and SQL Server? It is no surprise that PostGres has consistently ranked as one of the top four relational databases by multiple credible research studies comparing database engines.
Do you have a good caching strategy for your applications? Have you felt the pain of sticky sessions? Have you had a caching strategy that didn't work for you? Do you need a caching strategy that scales seamlessly with the least amount of effort? If the answer to any of these questions is a "yes," the good news is that you are in the right place.
Database technologies have undergone several generations of evolution, right from flat-file systems to relational databases to schemaless databases. Some people might say that traditional relational databases are a thing of the past, but that is not true for all the scenarios. Changing requirements and evolution of the internet has meant that new types of databases have emerged, but most have specific use cases, which makes it difficult to decide on which database should be used when. At the same time, different types of data models have emerged throughout the history of databases but only Relational and NoSQL models have prevailed.
Have you worked with multi-billion dollar consulting and recruiting companies? If yes, we are sure we can provide more quality services at a much more affordable rates. We have been fortunate to work directly with Microsoft product teams for many years. Our team includes Microsoft awarded Most Valuable Professionals, Azure Insiders, Docker Insiders, ASP.NET Insiders, Web API Advisors, Cosmos DB Insiders as well as experts in other Microsoft and notable open source technologies.