Amazon DynamoDB vs Riak

Overview

Amazon DynamoDB

Stacks4.0K

Followers3.2K

Votes195

Riak

Stacks103

Followers137

Votes44

GitHub Stars4.0K

Forks535

Amazon DynamoDB vs Riak: What are the differences?

Introduction Amazon DynamoDB and Riak are both NoSQL databases that offer high availability and scalability, but they have key differences in terms of data model, consistency, querying capabilities, and fault tolerance.

Data Model: One major difference between DynamoDB and Riak is their data model. DynamoDB follows a key-value data model, where each item has a primary key and optional additional attributes. Riak, on the other hand, uses a key-value and document data model, allowing for more complex and structured data storage.
Consistency: DynamoDB offers different consistency models to choose from, allowing developers to prioritize availability or consistency based on their application requirements. Riak, however, follows a default "eventually consistent" model, where updates may take some time to propagate across the cluster, ensuring high availability but sacrificing some consistency.
Querying Capabilities: DynamoDB provides a flexible querying mechanism using its Query and Scan APIs, allowing developers to retrieve data based on specific conditions and filters. Riak, in contrast, offers a simple key-based retrieval mechanism with support for secondary indexes, but lacks the rich querying capabilities provided by DynamoDB.
Fault Tolerance: DynamoDB is built on AWS infrastructure, which provides built-in fault-tolerance and replication across multiple Availability Zones. Riak, on the other hand, is designed to be distributed and fault-tolerant from the ground up, using a peer-to-peer architecture that distributes data across a cluster of nodes.
Data Replication: DynamoDB replicates data synchronously to three Availability Zones, ensuring durability and availability even in the event of a failure. Riak, however, uses a "write-once" model where writes are only sent to a single node, and then asynchronously replicated to other nodes in the background.
Concurrency Control: DynamoDB uses optimistic concurrency control, where conflicting updates are resolved based on the last writer wins principle. Riak, on the other hand, offers vector clocks as a means of conflict resolution, allowing diverged copies of data to be merged intelligently when they are subsequently reconciled.

In summary, Amazon DynamoDB and Riak differ in their data models, consistency models, querying capabilities, fault tolerance mechanisms, data replication strategies, and concurrency control mechanisms.

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Advice on Amazon DynamoDB, Riak

Doru

Solution Architect

Jun 9, 2019

Reviewon

Amazon 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.

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Detailed Comparison

Amazon DynamoDB	Riak
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.	Riak is a distributed database designed to deliver maximum data availability by distributing data across multiple servers. As long as your client can reach one Riak server, it should be able to write data. In most failure scenarios, the data you want to read should be available, although it may not be the most up-to-date version of that data.
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	-
Statistics
GitHub Stars -	GitHub Stars 4.0K
GitHub Forks -	GitHub Forks 535
Stacks 4.0K	Stacks 103
Followers 3.2K	Followers 137
Votes 195	Votes 44
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 14 High Performance 11 High Availability 9 Easy Scalability 5 Flexible 1 Multi datacenter deployments
Integrations
Amazon RDS for PostgreSQL PostgreSQL MySQL SQLite Azure Database for MySQL	No integrations available

What are some alternatives to Amazon DynamoDB, Riak?

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

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

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

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 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

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 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.

ArangoDB

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.

Related Comparisons

Amazon DynamoDB vs Riak: What are the differences?

Data Model: One major difference between DynamoDB and Riak is their data model. DynamoDB follows a key-value data model, where each item has a primary key and optional additional attributes. Riak, on the other hand, uses a key-value and document data model, allowing for more complex and structured data storage.
Consistency: DynamoDB offers different consistency models to choose from, allowing developers to prioritize availability or consistency based on their application requirements. Riak, however, follows a default "eventually consistent" model, where updates may take some time to propagate across the cluster, ensuring high availability but sacrificing some consistency.
Querying Capabilities: DynamoDB provides a flexible querying mechanism using its Query and Scan APIs, allowing developers to retrieve data based on specific conditions and filters. Riak, in contrast, offers a simple key-based retrieval mechanism with support for secondary indexes, but lacks the rich querying capabilities provided by DynamoDB.
Fault Tolerance: DynamoDB is built on AWS infrastructure, which provides built-in fault-tolerance and replication across multiple Availability Zones. Riak, on the other hand, is designed to be distributed and fault-tolerant from the ground up, using a peer-to-peer architecture that distributes data across a cluster of nodes.
Data Replication: DynamoDB replicates data synchronously to three Availability Zones, ensuring durability and availability even in the event of a failure. Riak, however, uses a "write-once" model where writes are only sent to a single node, and then asynchronously replicated to other nodes in the background.
Concurrency Control: DynamoDB uses optimistic concurrency control, where conflicting updates are resolved based on the last writer wins principle. Riak, on the other hand, offers vector clocks as a means of conflict resolution, allowing diverged copies of data to be merged intelligently when they are subsequently reconciled.

Amazon DynamoDB vs Riak

Overview