Carrot Search: Lingo4G: Comparison

Lingo4G and Lingo3G are independent and complementary products.
See the table below or contact us for some help choosing which one is best for you.

Lingo4G Lingo3G
Primary use case Processing of collections available in advance for indexing before clustering. Processing of small and medium collections of ad-hoc content, such as search results.
Maximum input collection size ~100 GB
Millions of documents
~10 MB
Thousands of documents
Architecture

Stateful. Lingo4G first needs to index all your documents and only then can it analyze the whole indexed collection of a subset of it. Including previously unseen documents in an analysis requires re-indexing.

The split into two phases allows Lingo4G to perform the expensive operations, such as tokenization of documents, only once during indexing.

Stateless. Lingo3G performs processing in one step, all documents provided on input will be immediately processed and disposed of.

The stateless paradigm makes it possible to process arbitrary and previously unseen documents. The cost is that the time-consuming operations, such as tokenization, will be repeated for each set of documents being processed.

See Lingo4G manual for more differences between Lingo4G and Lingo3G.

Easy to integrate, many tuning options, very fast and lightweight.

Stephan Schmid, CEO at Comcepta, Switzerland

Our evaluation found overwhelming support for using Lingo3G.

Dr James Thomas, Associate Director, EPPI-Centre, Social Science Research Unit, Institute of Education, London

I’ve shown two board members of our client company what our FoamTree-powered app does. Amazing what a good visualization can accomplish :-)

René de Vries, Managing Director at HowardsHome