DBMS > Amazon DynamoDB vs. etcd vs. FileMaker vs. Riak TS vs. VictoriaMetrics

System Properties Comparison Amazon DynamoDB vs. etcd vs. FileMaker vs. Riak TS vs. VictoriaMetrics

Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

A distributed reliable key-value store

FileMaker is a cross-platform RDBMS that includes a GUI frontend.

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

A fast, cost-effective and scalable Time Series DBMS and monitoring solution

Primary database model

Document store
Key-value store

Key-value store

Relational DBMS

Time Series DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	7.03
Rank	#54	Overall
	#5	Key-value stores

Score	47.91
Rank	#20	Overall
	#14	Relational DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Score	1.23
Rank	#172	Overall
	#15	Time Series DBMS

Website

aws.amazon.com/dynamodb

etcd.io
github.com/etcd-io/etcd

www.claris.com/filemaker

victoriametrics.com

Technical documentation

docs.aws.amazon.com/dynamodb

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

www.claris.com/resources/documentation

www.tiot.jp/riak-docs/riak/ts/latest

docs.victoriametrics.com
github.com/VictoriaMetrics/VictoriaMetrics/wiki

Developer

Amazon

Claris

a subsidiary of Apple

Open Source, formerly Basho Technologies

VictoriaMetrics

Initial release

2012

1983

2015

2018

Current release

3.4, August 2019

19.4.1, November 2021

3.0.0, September 2022

v1.91, May 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Erlang

Server operating systems

hosted

FreeBSD
Linux
Windows

experimental

iOS

client part only
Linux
OS X
Windows

Linux
OS X

FreeBSD
Linux
macOS
OpenBSD

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

A http query request can return the data in XML format

Secondary indexes

yes

restricted

SQL

Support of SQL

yes

via plugins

yes, limited

APIs and other access methods

RESTful HTTP API

gRPC
JSON over HTTP

Filemaker WebDirect
JDBC
ODBC

HTTP API
Native Erlang Interface

Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

PHP

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

yes

Erlang

Triggers

yes

by integration with AWS Lambda

yes, watching key changes

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

Source-replica replication, warm standby

since Version 14

selectable replication factor

Synchronous replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

ACID across one or more tables within a single AWS account and region

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

simple rights management via user accounts and connection to external directory services

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