The Accelerated move to Big Data Analytics and Cloud Are Leaving Some Vendors Behind.

By Hubert Yoshida posted 06-11-2019 00:00


The global big data market is expected to grow at a CAGR of 22.4% during the forecast period and reach USD 200 billion by 2024 according to MarketWatch estimates. Data analytics is expected to be the key driver for this market. However, the stocks of big data analytics vendors have been tanking in a way that is reminiscent of the dot com bust.


 It was only a week ago when I blogged about the cloud data management company MapR, closing its headquarters and laying off 122 employees. Now Cloudera, another cloud big data management company, announced reduced earnings and reduced outlook which drove its stock down over 38% to around $5. It was only in January of this year when Cloudera and Hortonworks, two of the biggest players in the Hadoop big data space, announced an all-stock merger, which was expected to give new life to these companies in the big data analytics market.

So, what is happening? It didn’t help that the CEO of MapR resigned abruptly and the CEO of Cloudera retired as the latest earnings report was released. Changing CEOs will require several quarters for these companies to rebuild credibility. Analysts point out that they have strong competition from the hyper cloud vendors, AWS, Azure and Google Cloud, which are able to provide more services and applications. The Infrastructure as a Service play has already been won by the large public cloud providers and now the race is on for big data analytics services. The recent acquisition of Tableau by SalesForce and Looker by Google, are indicative of a trend by public cloud providers moving to provide end to end big data analytics solutions across multiple clouds.

While Hybrid cloud provides an opportunity to augment public cloud offerings, companies like MapR and Cloudera will have upfront development and support costs which will impact cash flow. Cloudera is developing a Cloudera Data Platform (CDP) with Horton Works to support multi-function analytics: from streaming and big data ingest to IoT and machine learning and support every conceivable cloud delivery mechanism: private cloud, public cloud, multi-cloud, hybrid, on-prem and containerized deployments, all with a common metadata catalog and schema. Some analysts are speculating that customers want to move to the cloud faster than Cloudera can allow them. These customers do not have the luxury of waiting for and trialing CDP while there are other options that are available today.

Hitachi Vantara customers have several options for accelerating their movement to the cloud and big data analytics for structured and unstructured data. One approach is to develop a data lake with Pentaho and other best of breed data ingestion and data orchestration tools for big data analytics that can span multiple cloud delivery platforms with a common meta data catalog and schema. Pentaho’s low code approach can simplify and accelerate the implementation of big data analytics. Hitachi Vantara has taken this approach internally  for our enterprise data that need to reside within our private cloud

Another option from Hitachi Vantara is to use REAN Cloud ,a global Cloud Systems Integrator (CSI), Managed Service Provider (MSP) and Premier Consulting Partner in the Amazon Web Services (AWS) Partner Network (APN) and Microsoft's Azure Silver Partner membership. REAN Cloud offers consulting & professional services, including cloud strategy, assessment, cloud migration, and implementation to realize our customers’ vision. REAN Cloud provides a REAN Cloud Accelerated Migration Program (RAMP) which can accelerate the migration to public cloud from a matter of weeks to days with their automated services and migration consulting expertise. Migration to the hyper cloud vendors enables the use of their menu of analytics tools. REAN Cloud incudes 47Lining an AWS Advanced Consulting Partner with Big Data Competency designation. 47Lining develops big data solutions and delivers big data managed services built from underlying AWS building blocks like Amazon Redshift, Kinesis, S3, DynamoDB, Machine Learning and Elastic MapReduce.

A full transition to the cloud has proved more challenging than anticipated and many companies are looking to hybrid cloud solutions to transition to the cloud at their own pace and at a lower risk and cost. Companies are looking for DataOps tools and platforms, and systems integrators that can help them create data lakes and deliver big data analytics in a timely manner. They want proven vendors who will be with them for the long term and who already have the platforms and services for hybrid cloud and big data analytics that can work within the ecosystem of public and private clouds.