Diffbot vs Weka

Diffbot uses AI models to turn unstructured web content into linked knowledge through a set of data services. Extract classifies a page and returns structured JSON using a standard page type and ontology. Crawl starts with seed URLs, visits sites, and collects extracted pages in structured datasets. Natural Language resolves entities, relationships, coreferences, salience, and sentiment in plain text. The Knowledge Graph supports structured queries about companies, people, news, and other public web entities. Web Search provides an API and a self-hostable search index for a machine or cloud, including offline use; Diffbot says closed media sites such as Facebook, Reddit, LinkedIn, and Instagram are generally off limits. Python and TypeScript libraries and agent skills are listed as interfaces. The free plan provides 10,000 credits per month, all four APIs, and up to 5 requests per minute without a credit card. It returns a 429 Quota Exceeded response after the credit allowance or rate limit is reached, with quotas resetting at the start of each billing period. Startup costs $299 a month. Diffbot lists API, self-hosted, and web platforms.

Weka is open-source machine-learning software for building and evaluating models, with support for forecasting and time-series modeling. It is available free under the GNU General Public License, with Weka 3.8 as the stable release and 3.9 as the development version. The stable branch receives fixes and feature updates intended to preserve compatibility; development builds may introduce breaking changes. Weka provides a Java API, Javadoc for its API and command-line parameters, and can also be used through Jupyter notebooks. Official releases require Java 8 or later. Downloads are listed for Windows, Mac OS, and Linux, with Intel and ARM options. Both branches include a package manager for community extensions, though installing packages requires internet access. The software includes built-in help and a comprehensive manual, with additional assistance through documentation, mailing list archives, forums, and a mailing list. Distributed derivative works must use the GPL; commercial projects needing Weka code in a non-GPL program may be able to obtain a suitable license. Models serialized in version 3.7 are incompatible with 3.8, and the migrator has an exception for RandomForest.