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  1. Stackups
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  4. Databases
  5. ArangoDB vs Serverless

ArangoDB vs Serverless

OverviewDecisionsComparisonAlternatives

Overview

ArangoDB
ArangoDB
Stacks273
Followers442
Votes192
Serverless
Serverless
Stacks2.2K
Followers1.2K
Votes28
GitHub Stars46.9K
Forks5.7K

ArangoDB vs Serverless: What are the differences?

Developers describe ArangoDB as "A distributed open-source database with a flexible data model for documents, graphs, and key-values". A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions. On the other hand, Serverless is detailed as "The most widely-adopted toolkit for building serverless applications". Build applications comprised of microservices that run in response to events, auto-scale for you, and only charge you when they run. This lowers the total cost of maintaining your apps, enabling you to build more logic, faster. The Framework uses new event-driven compute services, like AWS Lambda, Google CloudFunctions, and more.

ArangoDB and Serverless are primarily classified as "Databases" and "Serverless / Task Processing" tools respectively.

"Grahps and documents in one DB" is the top reason why over 24 developers like ArangoDB, while over 10 developers mention "API integration " as the leading cause for choosing Serverless.

ArangoDB and Serverless are both open source tools. It seems that Serverless with 30.5K GitHub stars and 3.38K forks on GitHub has more adoption than ArangoDB with 8.14K GitHub stars and 575 GitHub forks.

Droplr, Plista GmbH, and Hammerhead are some of the popular companies that use Serverless, whereas ArangoDB is used by AresRPG, Stepsize, and Brainhub. Serverless has a broader approval, being mentioned in 112 company stacks & 43 developers stacks; compared to ArangoDB, which is listed in 11 company stacks and 13 developer stacks.

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Advice on ArangoDB, Serverless

Tim
Tim

CTO at Checkly Inc.

Sep 18, 2019

Needs adviceonHerokuHerokuAWS LambdaAWS Lambda

When adding a new feature to Checkly rearchitecting some older piece, I tend to pick Heroku for rolling it out. But not always, because sometimes I pick AWS Lambda . The short story:

  • Developer Experience trumps everything.
  • AWS Lambda is cheap. Up to a limit though. This impact not only your wallet.
  • If you need geographic spread, AWS is lonely at the top.

The setup

Recently, I was doing a brainstorm at a startup here in Berlin on the future of their infrastructure. They were ready to move on from their initial, almost 100% Ec2 + Chef based setup. Everything was on the table. But we crossed out a lot quite quickly:

  • Pure, uncut, self hosted Kubernetes — way too much complexity
  • Managed Kubernetes in various flavors — still too much complexity
  • Zeit — Maybe, but no Docker support
  • Elastic Beanstalk — Maybe, bit old but does the job
  • Heroku
  • Lambda

It became clear a mix of PaaS and FaaS was the way to go. What a surprise! That is exactly what I use for Checkly! But when do you pick which model?

I chopped that question up into the following categories:

  • Developer Experience / DX 🤓
  • Ops Experience / OX 🐂 (?)
  • Cost 💵
  • Lock in 🔐

Read the full post linked below for all details

357k views357k
Comments

Detailed Comparison

ArangoDB
ArangoDB
Serverless
Serverless

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

Build applications comprised of microservices that run in response to events, auto-scale for you, and only charge you when they run. This lowers the total cost of maintaining your apps, enabling you to build more logic, faster. The Framework uses new event-driven compute services, like AWS Lambda, Google CloudFunctions, and more.

multi-model nosql db; acid; transactions; javascript; database; nosql; sharding; replication; query language; joins; aql; documents; graphs; key-values; graphdb
-
Statistics
GitHub Stars
-
GitHub Stars
46.9K
GitHub Forks
-
GitHub Forks
5.7K
Stacks
273
Stacks
2.2K
Followers
442
Followers
1.2K
Votes
192
Votes
28
Pros & Cons
Pros
  • 37
    Grahps and documents in one DB
  • 26
    Intuitive and rich query language
  • 25
    Good documentation
  • 25
    Open source
  • 21
    Joins for collections
Cons
  • 3
    Web ui has still room for improvement
  • 2
    No support for blueprints standard, using custom AQL
Pros
  • 14
    API integration
  • 7
    Supports cloud functions for Google, Azure, and IBM
  • 3
    Lower cost
  • 1
    3. Simplified Management for developers to focus on cod
  • 1
    Openwhisk
Integrations
No integrations available
Azure Functions
Azure Functions
AWS Lambda
AWS Lambda
Amazon API Gateway
Amazon API Gateway

What are some alternatives to ArangoDB, Serverless?

MongoDB

MongoDB

MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.

MySQL

MySQL

The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

PostgreSQL

PostgreSQL

PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.

Microsoft SQL Server

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

Memcached

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

AWS Lambda

AWS Lambda

AWS Lambda is a compute service that runs your code in response to events and automatically manages the underlying compute resources for you. You can use AWS Lambda to extend other AWS services with custom logic, or create your own back-end services that operate at AWS scale, performance, and security.

RethinkDB

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

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