Cloudera vs Pivotal

Cloudera helps you become information-driven by leveraging the best of the open source community with the enterprise capabilities you need to succeed with Apache Hadoop in your organization. Designed specifically for mission-critical environments, Cloudera Enterprise includes CDH, the world’s most popular open source Hadoop-based platform, as well as advanced system management and data management tools plus dedicated support and community advocacy from our world-class team of Hadoop developers and experts. Cloudera is your partner on the path to big data.
Pivotal is the leading enterprise PaaS, powered by Cloud Foundry. It delivers an always-available, turnkey experience for scaling and updating PaaS on the private cloud. Pivotal is enabling the creation of modern software applications that leverage big & fast data – on a single, cloud independent platform.
Cloudera vs Pivotal in our news:

2018 - Big Data platforms Cloudera and Hortonworks merge

Over the years, Hadoop, the once high-flying open-source platform, gave rise to many companies and an ecosystem of vendors emerged. The problem with Hadoop was the sheer complexity of it. That’s where companies like Hortonworks and Cloudera came in. They packaged it for IT departments that wanted the advantage of a big data processing platform, but didn’t necessarily want to build Hadoop from scratch. These companies offered different ways of helping to attack that complexity, but over time, with all the cloud-based big data solutions, rolling a Hadoop system seemed futile, even with the help of companies like Cloudera and Hortonworks. Today the two companies announced are merging in a deal worth $5.2 billion. The combined companies will boast 2,500 customers, $720 million in revenue and $500 million in cash with no debt, according to the companies.

2015 - Google partners with Cloudera to bring Cloud Dataflow to Apache Spark

Google announced that it has teamed up with the Hadoop specialists at Cloudera to bring its Cloud Dataflow programming model to Apache’s Spark data processing engine. With Google Cloud Dataflow, developers can create and monitor data processing pipelines without having to worry about the underlying data processing cluster. As Google likes to stress, the service evolved out of the company’s internal tools for processing large datasets at Internet scale. Not all data processing tasks are the same, though, and sometimes you may want to run a task in the cloud or on premise or on different processing engines. With Cloud Dataflow — in its ideal state — data analysts will be able use the same system for creating their pipelines, no matter the underlying architecture they want to run them on.

2014 - Cloudera helps to manage Hadoop on Amazon cloud

Hadoop vendor Cloudera announced a new product called Director that will make it easier for customers to manage their Hadoop clusters on the Amazon Web Services cloud. Senior Director of Product Marketing Clarke Patterson acknowledged that has not been easy to date while still maintaining the breadth of capabilities. Although there’s no difference between the cloud version and the on-premises version of the software, he added, the Director interface is designed to be self-service and includes cloud-specific capabilities such as instance-tracking so administrators can keep an eye on whose cloud instances are costing what.

2014 - Cloudera bought data-visualization startup DataPad to take on Pivotal

Cloud-based big data platform Cloudera has acquired a data-visualization startup DataPad which specializes in data analysis using the Python programming language. As Hadoop competition heats up, Cloudera might be ramping up its Python tooling in order to attract more data scientists and developers (DataPad co-founders are known in the data science community for having developed a Python-based data analysis library Pandas). It's not surprising considering the billions of dollars up for play in the commercial Hadoop market. Cloudera, Hortonworks, MapR, Pivotal and more are all trying to win over as many users as they can for their respective flavors of Hadoop and general big data infrastructure. Spreading the cheerleading base beyond IT staff and systems architects, to include the people actually developing applications and doing data analysis within the company, is a good way to help ensure your stuff is the stuff that gets used.

2014 - Pivotal brings its cloud services to Mobile to keep up with Cloudera

Pivotal, the enterprise cloud platform, is launching new services for mobile development that are designed to work side-by-side with the company’s previously announced data services. The new CF Mobile Service will include push notifications, an API gateway and data-sync services. The service also offers IT the ability to set different policies and service level agreements to ensure that the data remain under the enterprise’s control. Pivotal CF is based on the company’s open source Cloud Foundry PaaS. Given its heritage, it’s no surprise that Pivotal CF supports a wide range of open-source tools (and especially databases), including database services like MongoDB, Riak, Apache Cassandra and the Neo4j graph database.

2014 - GE becomes Big Data provider to catch up with Heroku

Last year, General Electric invested $105 million in Big Data platform Pivotal. Now it’s
starting to deploy Pivotal’s big data analytics capabilities both in
house and to buyers of its jet engines. Using Pivotal’s Big Data Suite and EMC’s appliances, GE built out its own capability first for its aviation group in 90 days, which then connected up to 25 airline customers to make use of all that data and analytics. Aggregating data from 15,000 flights yielded 14 GB of information per flight, which could then be analyzed in a reasonable amount of time. Using traditional methods it could take 30 days to sort through data required to figure out a maintenance issue. Now major analytics can be run in 20 minutes.

2014 - Pivotal adds new enterprise features to its PaaS platform to compete with HP Vertica

Pivotal, the provider of Cloud Foundry based PaaS platform is adding features to appeal to big companies wanting to build and deploy their own applications across multiple clouds. For example, Pivotal CF users can now deploy applications in dual availability zones across clouds to boost redundancy and it has gussied up its dashboards to reflect real-time application status. PivotalCF is part of Pivotal’s push which also incorporates other technologies contributed by Pivotal parent companies EMC and VMware. They include EMC’s Greenplum big data analytics, Pivotal Labs’ agile development, Cetas analytics, VMware’s vFabric and Cloud Foundry.