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  1. Stackups
  2. Application & Data
  3. NoSQL Databases
  4. NOSQL Database As A Service
  5. Amazon DynamoDB vs ArangoDB

Amazon DynamoDB vs ArangoDB

OverviewDecisionsComparisonAlternatives

Overview

Amazon DynamoDB
Amazon DynamoDB
Stacks4.0K
Followers3.2K
Votes195
ArangoDB
ArangoDB
Stacks273
Followers442
Votes192

Amazon DynamoDB vs ArangoDB: What are the differences?

Amazon DynamoDB: Fully managed NoSQL database service. All data items are stored on Solid State Drives (SSDs), and are replicated across 3 Availability Zones for high availability and durability. With DynamoDB, you can offload the administrative burden of operating and scaling a highly available distributed database cluster, while paying a low price for only what you use; ArangoDB: 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.

Amazon DynamoDB can be classified as a tool in the "NoSQL Database as a Service" category, while ArangoDB is grouped under "Databases".

Some of the features offered by Amazon DynamoDB are:

  • Automated Storage Scaling – There is no limit to the amount of data you can store in a DynamoDB table, and the service automatically allocates more storage, as you store more data using the DynamoDB write APIs.
  • Provisioned Throughput – When creating a table, simply specify how much request capacity you require. DynamoDB allocates dedicated resources to your table to meet your performance requirements, and automatically partitions data over a sufficient number of servers to meet your request capacity. If your throughput requirements change, simply update your table's request capacity using the AWS Management Console or the Amazon DynamoDB APIs. You are still able to achieve your prior throughput levels while scaling is underway.
  • Fully Distributed, Shared Nothing Architecture – Amazon DynamoDB scales horizontally and can seamlessly scale a single table over hundreds of servers.

On the other hand, ArangoDB provides the following key features:

  • multi-model nosql db
  • acid
  • transactions

"Predictable performance and cost" is the top reason why over 53 developers like Amazon DynamoDB, while over 24 developers mention "Grahps and documents in one DB" as the leading cause for choosing ArangoDB.

ArangoDB is an open source tool with 8.14K GitHub stars and 575 GitHub forks. Here's a link to ArangoDB's open source repository on GitHub.

Netflix, Medium, and Intuit are some of the popular companies that use Amazon DynamoDB, whereas ArangoDB is used by AresRPG, Stepsize, and Brainhub. Amazon DynamoDB has a broader approval, being mentioned in 433 company stacks & 173 developers stacks; compared to ArangoDB, which is listed in 11 company stacks and 13 developer stacks.

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Advice on Amazon DynamoDB, ArangoDB

Doru
Doru

Solution Architect

Jun 9, 2019

ReviewonAmazon DynamoDBAmazon DynamoDB

I use Amazon DynamoDB because it integrates seamlessly with other AWS SaaS solutions and if cost is the primary concern early on, then this will be a better choice when compared to AWS RDS or any other solution that requires the creation of a HA cluster of IaaS components that will cost money just for being there, the costs not being influenced primarily by usage.

1.34k views1.34k
Comments
akash
akash

Aug 27, 2020

Needs adviceonCloud FirestoreCloud FirestoreFirebase Realtime DatabaseFirebase Realtime DatabaseAmazon DynamoDBAmazon DynamoDB

We are building a social media app, where users will post images, like their post, and make friends based on their interest. We are currently using Cloud Firestore and Firebase Realtime Database. We are looking for another database like Amazon DynamoDB; how much this decision can be efficient in terms of pricing and overhead?

199k views199k
Comments

Detailed Comparison

Amazon DynamoDB
Amazon DynamoDB
ArangoDB
ArangoDB

With it , you can offload the administrative burden of operating and scaling a highly available distributed database cluster, while paying a low price for only what you use.

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.

Automated Storage Scaling – There is no limit to the amount of data you can store in a DynamoDB table, and the service automatically allocates more storage, as you store more data using the DynamoDB write APIs;Provisioned Throughput – When creating a table, simply specify how much request capacity you require. DynamoDB allocates dedicated resources to your table to meet your performance requirements, and automatically partitions data over a sufficient number of servers to meet your request capacity;Fully Distributed, Shared Nothing Architecture
multi-model nosql db; acid; transactions; javascript; database; nosql; sharding; replication; query language; joins; aql; documents; graphs; key-values; graphdb
Statistics
Stacks
4.0K
Stacks
273
Followers
3.2K
Followers
442
Votes
195
Votes
192
Pros & Cons
Pros
  • 62
    Predictable performance and cost
  • 56
    Scalable
  • 35
    Native JSON Support
  • 21
    AWS Free Tier
  • 7
    Fast
Cons
  • 4
    Only sequential access for paginate data
  • 1
    Scaling
  • 1
    Document Limit Size
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
Integrations
Amazon RDS for PostgreSQL
Amazon RDS for PostgreSQL
PostgreSQL
PostgreSQL
MySQL
MySQL
SQLite
SQLite
Azure Database for MySQL
Azure Database for MySQL
No integrations available

What are some alternatives to Amazon DynamoDB, ArangoDB?

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.

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.

InfluxDB

InfluxDB

InfluxDB is a scalable datastore for metrics, events, and real-time analytics. It has a built-in HTTP API so you don't have to write any server side code to get up and running. InfluxDB is designed to be scalable, simple to install and manage, and fast to get data in and out.

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