ArangoDB in San Francisco / Bay Area

02GeneralTags:

Join parts of the ArangoDB team in San Francisco. Max and Claudius are visiting the Bay Area from mid-February till end of March. Starting with the StrataConf in San Jose, Feb 17–20, 2015 Max and Claudius want to meet people, start cooperations, visit meetups and tell people in the Bay Area about ArangoDB.

If you know any hackerspaces we definitely should go, drop us a line and we will try to be there. We would be happy to see some of you guys in person and to respond to every question you may have about ArangoDB.

New Plugin for ElasticSearch by ArangoDB

01GeneralTags:

ArangoDB River Plugin for ElasticSearch

ArangoDB offers now a plugin for automated data transfer from ArangoDB into ElasticSearch.

If you want to benefit from ElasticSearch’s full text search capabilities for your ArangoDB document data, the easiest way to do so is to use this new plugin.
Implementing the push approach, otherwise, would make it necessary to write your own indexer, using your favorite programming language.
The ArangoDB river plugin software is an initial alpha version and licensed under the Apache 2 license.
More info

Is UNQL Dead?

04Architecture, Query LanguageTags: ,
Note: We changed the name of the database in May 2012. AvocadoDB is now called ArangoDB.

UNQL started with quite some hype last year. However, after some burst of activity the project came to a hold. So it seems, that – at least as a project – UNQL has been a failure. IMHO one of the major issues with the current UNQL is, that it tries to cover everything in NoSQL, from key-value stores to document-stores to graph-database. Basically you end up with greatest common divisor – namely key-value access. But with graph structures and also document-structures you really want to supports joins, paths or some sort of sub-structures.

Apart from all the technical and theoretical benefits of SQL and what advantages the underlying theory has to offer, the major plus from an users point of view is that it is readable. You simple can see an SQL statement – be it in C, Java, Ruby – and understand what is going on. It is declarative, not imperative. With other imperative solution, like a fluent interface or a map-reduce, you need to understand the underlying syntax or language. With SQL you only need to understand English – at least most of the time.

And here I think is where UNQL is totally right. We need something similar for the NoSQL world. But it should not try to be a “fits all situation”. It should be a fit for 80% of the problems. For simple key-values stores a fluent-interface is indeed enough. For very complex graph traversals a traversal program must be written. For very complex map-reduces you might need to write a program – but check out Google’s talk (www.nosql-matters.org/program) about NoNoSQL. There they describe why they are developing a SQL-like interface for Map/Reduce.

In my experience most of the time you have a set of collections holding different “types” of documents with some relations between them. One of the biggest advantages of document stores or graph databases is that you can have lists and sub-objects. The problem with SQL is, that it has no good way to deal with these structures. So I believe UNQL would be quite successful if it would concentrate on these strong advantages of NoSQL, instead of trying to unify everything – especially after hear Jan’s talk about a document query language at the NoSQL Cologne UG (an English version is also available).