Cazton has been a pioneer in Big Data. Our team includes but not limited to Big Data Engineers, Distributed Systems Engineer, Data Scientists, Hadoop Experts, Spark Experts, Spark.NET Experts, Kafka Experts have years of experience and strong analytical and problem-solving skills. Our experts have hands-on experience with Big Data technologies that includes Hadoop, Spark, HIVE, HBase, Kafka, Impala, PIG, Zookeeper, Cassandra. NoSQL databases like Couchbase, MongoDB and have proven record building solid production level software on various Big data technologies. Contact us now to learn more about our big data services.
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.
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.
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
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.
The evolution of database technologies has been exceptional. Right from the first pre-stage flat-file systems to relational and object-relational databases to NoSQL databases, database technology has gone through several generations and its history has spread over more than 50 years now. A time has come when database technology has taken the next step forward to become more scalable, globally distributed and multi-model. Welcome to the new world of Cosmos DB!
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)?
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.
Did you know relational databases can scale up, but have a hard time scaling out? NoSQL databases, on the other hand, are meant to scale out with commodity-grade hardware. Many organizations prefer using NoSQL over SQL databases as it offers a great set of features. There are different types of NoSQL databases available including Key-Value Store, Document Databases, Column-Family Databases, Graph Databases and Full-Text Search Engine Databases.
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.
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.
Search is one of the most important aspects in any application. Could you imagine Amazon, one of the world's largest e-commerce websites, without a search functionality? It would be nearly impossible to find products if we had to look for them manually. A robust search in this case is the key towards best user experience, increased customer traffic, growth in sales and generation of customer data, which is invaluable for such a big organization.
Search is one of the most important tools in any web application. Having a robust and fool-proof search system can boost your business growth in many ways. One such technology that empowers search is called Elasticsearch. Unlike traditional RDBMS, Elasticsearch is designed to allow full-text searching. It allows you to create your own search-engine that is fast, powerful and scalable. In addition to web searches, Elasticsearch is also used for log analysis and big data analytics.