Martin Heller

Contributing Editor

Martin Heller is a contributing editor and reviewer for InfoWorld. Formerly a web and Windows programming consultant, he developed databases, software, and websites from his office in Andover, Massachusetts, from 1986 to 2010. More recently, he has served as VP of technology and education at Alpha Software and chairman and CEO at Tubifi. Disclosure: He also writes for Hewlett-Packard's TechBeacon marketing website.

DSE Graph review: Graph database does double duty

DSE Graph review: Graph database does double duty

DSE Graph provides high-performance OLTP and OLAP graph operations, right alongside the DataStax Enterprise column store

How to choose the right database for your application

How to choose the right database for your application

From performance to programmability, the right database makes all the difference. Here are 12 key questions to guide your selection

What is SQL? The first language of data analysis

What is SQL? The first language of data analysis

SQL is neither the fastest nor the most elegant way to talk to databases, but it is the best way we have. Here’s why

Qubole review: Self-service big data analytics

Qubole review: Self-service big data analytics

Cloud-native data platform puts Spark, Presto, Hive, and Airflow at your fingertips, while controlling your cloud spending

Rockset review: Real-time SQL for operational data

Rockset review: Real-time SQL for operational data

One-of-a-kind database for operational analytics analyzes gigabytes to terabytes of recent, real-time, and streaming data in milliseconds

MongoDB vs. MySQL: How to choose

MongoDB vs. MySQL: How to choose

MongoDB and MySQL are the leading open source NoSQL and relational databases, respectively. Which is best for your application?

The best open source software of 2019

The best open source software of 2019

InfoWorld recognizes the leading open source projects for software development, cloud computing, data analytics, and machine learning

Visual Studio Code vs. Sublime Text: How to choose

Visual Studio Code vs. Sublime Text: How to choose

Do you want a maximum-flexible editor with just the right IDE features, or the fastest and most efficient editor you can find? You can have both

Visual Studio Code vs. Visual Studio: How to choose

Visual Studio Code vs. Visual Studio: How to choose

Deciding between Visual Studio Code and Visual Studio may depend as much on your work style as on the language support and features you need. Here’s how to decide

Snowflake review: A data warehouse made better in the cloud

Snowflake review: A data warehouse made better in the cloud

A fast, no-fuss data warehouse as a service, Snowflake scales dynamically to give you the performance you need exactly when you need it

Semi-supervised learning explained

Semi-supervised learning explained

Using a machine learning model’s own predictions on unlabeled data to add to the labeled data set sometimes improves accuracy, but not always

PyTorch vs. TensorFlow: How to choose

PyTorch vs. TensorFlow: How to choose

If you actually need a deep learning model, PyTorch and TensorFlow are the two leading options

Automated machine learning or AutoML explained

Automated machine learning or AutoML explained

AutoML frameworks and services eliminate the need for skilled data scientists to build machine learning and deep learning models

Couchbase review: A smart NoSQL database

Couchbase review: A smart NoSQL database

Flexible, distributed document database offers an easy query language, mobile synch, independently scalable services, and strong consistency within a cluster

The best NoSQL databases

The best NoSQL databases

Highly flexible and hugely scalable, NoSQL databases offer a range of data models and consistency options to suit your application

Unsupervised learning explained

Unsupervised learning explained

Unsupervised learning is used mainly to discover patterns and detect outliers in data today, but could lead to general-purpose AI tomorrow

The best graph databases

The best graph databases

These stellar databases combine horizontal scalability with highly efficient engines for storing and analyzing connected data

The best machine learning and deep learning libraries

The best machine learning and deep learning libraries

TensorFlow, Spark MLlib, Scikit-learn, PyTorch, MXNet, and Keras shine for building and training machine learning and deep learning models

The best distributed relational databases

The best distributed relational databases

These SQL relational databases offer both horizontal scalability and support for ACID transactions—some on a global scale

TensorFlow 2 review: Easier machine learning

TensorFlow 2 review: Easier machine learning

Now more platform than toolkit, TensorFlow has made strides in everything from ease of use to distributed training and deployment

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