Review: Google Bigtable scales with ease

When Google announced a beta test of Cloud Bigtable in May 2015, the new database as a service drew lots of interest from people who had been using HBase or Cassandra. This was not surprising. Now that Cloud Bigtable has become generally available, it should gain even more attention from people who would like to collect and analyze extremely large data sets without having to build, run, and sweat the details of scaling out their own enormous database clusters.

Cloud Bigtable is a public, highly scalable, column-oriented NoSQL database as a service that uses the very same code as Google’s internal version, which Google invented in the early 2000s and published a paper about in 2006. Bigtable was and is the underlying database for many Google services, including Search, Analytics, Maps, and Gmail.

Source: InfoWorld Big Data

Review: 6 machine learning clouds

What we call machine learning can take many forms. The purest form offers the analyst a set of data exploration tools, a choice of ML models, robust solution algorithms, and a way to use the solutions for predictions. The Amazon, Microsoft, Databricks, Google, and IBM clouds all offer prediction APIs that give the analyst various amounts of control. HPE Haven OnDemand offers a limited prediction API for binary classification problems.

Not every machine learning problem has to be solved from scratch, however. Some problems can be trained on a sufficiently large sample to be more widely applicable. For example, speech-to-text, text-to-speech, text analytics, and face recognition are problems for which “canned” solutions often work. Not surprising, a number of machine learning cloud providers offer these capabilities through an API, allowing developers to incorporate them in their applications.

Source: InfoWorld Big Data

Review: HPE’s machine learning cloud overpromises, underdelivers

Developers longing to build more intelligent, more proactive, more personalized apps seem to gain more options with every passing day. With Haven OnDemand, Hewlett-Packard Enterprise (HPE) has joined the applied machine learning fray, competing directly with IBM Watson Services, Microsoft Cortana Analytics Suite, and several Google ML-based APIs.

Haven OnDemand is a platform for building cognitive computing solutions using text analysis, speech recognition, image analysis, indexing, and search APIs. While IBM based its cognitive computing/machine learning cloud services primarily on Watson, the “Jeopardy” winner, HPE based its recently announced Haven OnDemand services primarily on IDOL, its enterprise search engine.

Source: InfoWorld Big Data