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Great to know your database scales and database vendors like ArangoDB add some statistics on node / cluster health directly in their products.
But running a bunch of different servers and applications you need a central hub to collect monitoring data from all services running. In a series of recipes Willi shows how you could easily add monitoring capabilities to NoSQL databases like ArangoDB using collectd with the cURL JSON plugin. More info
Contained in 2.5 are some small but useful AQL language improvements plus several AQL optimizer improvements.
We are working on further AQL improvements for 2.5, but work is still ongoing. This post summarizes the improvements that are already completed and will be shipped with the initial ArangoDB 2.5 release.
This version is deprecated. Download the new version of ArangoDB
In ArangoDB 2.5, hash and skiplist indexes can optionally be made sparse.
Such sparse indexes will exclude documents in which at least one of the index attributes is either not set or has a value of null. Declaring an index as sparse can provide great savings in memory and index creation CPU time for some cases.
In the upcoming ArangoDB 2.5 (current devel branch) a new optimizer rule move-calculations-down was added. Jan showcases in his latest blog post how queries with calculations could benefit from this new optimiser rule.
Read in Jan’s blog how this rule could accelerate your queries
More than two years ago, we compared the bulk insert performance of ArangoDB, CouchDB and MongoDB in a blog post.
The original blog post dates back to the times of ArangoDB 1.1-alpha. We have been asked several times to re-run the tests with the current versions of the databases. So here we go.
With ArangoDB 2.3 now getting into the beta stage, it’s time to spread the word about new features and improvements.
Today’s post will be about the changes made to non-unique hash indexes.
ArangoDB offers a few APIs to insert documents. First, there is an HTTP API for bulk document imports. This API was already covered in another post. In general, the bulk import API should always be used when the task is to create many documents into a collection at once, as fast as possible. This works well if the documents are known in advance, e.g. when importing data from a file.
ArangoDB 1.1 will come with a new API for batch requests. This batch request API allows clients to send multiple requests to the ArangoDB server inside one multipart HTTP request. The server will then decompose the multipart request into the individual parts and process them as if they were sent individually. The communication layer can sustain up-to 800.000 requests/second – but absolute numbers strongly depend on the number of cores, the type of the requests, network connections and other factors. More important are the relative numbers: Depending on your use-case you can reduce insert/update times by 80%.
More info