Introducing the new ArangoDB Java driver with load balancing and advanced fallback

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The newest release 4.3.2 of the official ArangoDB Java driver comes with load balancing for cluster setups and advanced fallback mechanics.

Load balancing strategies

Round robin

There are two different strategies for load balancing that the Java driver provides. The first and most common strategy is the round robin way. Round robin does, what the name already assumes, a round robin load balancing where a list of known coordinators in the cluster is iterated through. Each database operation uses a different coordinator than the one before.

Most of the database operations can be handled by this simple logic. But for AQL queries we need something smarter. We have to stick to a specific coordinator when performing AQL queries where its result is not fully returned in a single response. In this case, ArangoDB creates state in form of a local cursor on the coordinator, the initial query was sent to. Every following request to get more batches of the result has to go to the same coordinator. Different to most simple standalone load balancer the driver is able to take care of that.
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ArangoDB Named Best Free Graph Database by G2 Crowd Users

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ArangoDB named by G2 Crowd users as the most popular graph database used today.

ArangoDB has been identified as the highest rated graph database, based on its high levels of customer satisfaction and likeliness to recommend ratings from real G2 Crowd users.

ArangoDB received a near perfect 4.9 out of 5 star average for user satisfaction for its free platform across its 24 user reviews. ArangoDB users point to the database’s query language, availability and storage as the three most liked features of the product. Read more

Introduction to Fuerte – The ArangoDB C++ Driver

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In this post, we will introduce you to our new ArangoDB C++ diver fuerte. fuerte allows you to communicate via HTTP and VST with ArangoDB instances. You will learn how to create collections, insert documents, retrieve documents, write AQL Queries and how to use the asynchronous API of the driver.

Requirements (Running the sample)

Please download and inspect the sample described in this post. The sample consists of a C++ – Example Source Code – File and a CMakeLists.txt. You need to install the fuerte diver, which can be found on github, into your system before compiling the sample. Please follow the instructions provided in the drivers README.md. Read More

Performance analysis with pyArango: Part III Measuring possible capacity with usage Scenarios

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So you measured and tuned your system like described in the Part I and Part II of these blog post series. Now you want to get some figures how many end users your system will be able to serve. Therefore you define “scenarios” which will be typical for what your users do.
One such a user scenario could i.e. be:

  • log in
  • do something
  • log out

Since your users won’t nicely queue up and wait for other users to finish their business, the pace you need to test your defined system is “starting n scenarios every second”. Many scenarios simulating different users may be running in parallel. If your scenario would require 10 seconds to finish, and you’d start 1 per second, that means that your system needs to be capable to process 10 users in parallel. If it can’t handle that, you will see that more than 10 sessions are running in parallel, and the time required to handle such a scenario will lengthen. You will see the server resource usage go up and up, and finally have it burst in flames.
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Auto-Generate GraphQL for ArangoDB

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Currently, querying ArangoDB with GraphQL requires building a GraphQL.js schema. This is tedious and the resulting JavaScript schema file can be long and bulky. Here we will demonstrate a short proof of concept that reduces the user related part to only defining the GraphQL IDL file and simple AQL queries.

The Apollo GraphQL project built a library that takes a GraphQL IDL and resolver functions to build a GraphQL.js schema. Resolve functions are called by GraphQL to get the actual data from the database. I modified the library in the way that before the resolvers are added, I read the IDL AST and create resolver functions. Read more

Performance analysis with pyArango: Part II
Inspecting transactions

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Following the previous blog post on performance analysis with pyArango, where we had a look at graphing using statsd for simple queries, we will now dig deeper into inspecting transactions. At first, we split the initialization code and the test code.

Initialisation code

We load the collection with simple documents. We create an index on one of the two attributes: Read more

Performance analysis using pyArango Part I

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Usually, your application will persist of a set of queries on ArangoDB for one scenario (i.e. displaying your user’s account information etc.) When you want to make your application scale, you’d fire requests on it, and see how it behaves. Depending on internal processes execution times of these scenarios vary a bit.

We will take intervals of 10 seconds, and graph the values we will get there:

  • average – all times measured during the interval, divided by the count.
  • minimum – fastest requests
  • maximum – slowest requests
  • the time “most” aka 95% of your users may expect an answer within – this is called 95% percentile

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Sorting number strings numerically

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Recently I gave a talk about ArangoDB in front of a community of mathematicians. I advertised that nearly arbitrary data can “easily” be stored in a JSON based document store. The moment I had uttered the word “easily”, one of them asked about long integers. And if a mathematician says “long integer” they do not mean 64bit but “properly long”. He actually wanted to store orders of finite groups. I said one should use a JSON UTF-8 string for this but I should have seen the next question coming because he then wanted that a sorted index would actually sort the documents by the numerical value stored in the string. But most databases – and ArangoDB is no exception here – will compare UTF-8 strings lexicographically (dictionary order). Read more

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