DBMS > Amazon DocumentDB vs. etcd vs. GeoMesa vs. Machbase Neo vs. Microsoft Azure Cosmos DB

System Properties Comparison Amazon DocumentDB vs. etcd vs. GeoMesa vs. Machbase Neo vs. Microsoft Azure Cosmos DB

Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

A distributed reliable key-value store

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

TimeSeries DBMS for AIoT and BigData

Globally distributed, horizontally scalable, multi-model database service

Primary database model

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Spatial DBMS

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

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	7.25
Rank	#54	Overall
	#5	Key-value stores

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Website

aws.amazon.com/documentdb

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

www.geomesa.org

machbase.com

azure.microsoft.com/services/cosmos-db

Technical documentation

aws.amazon.com/documentdb/resources

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

www.geomesa.org/documentation/stable/user/index.html

machbase.com/dbms

learn.microsoft.com/azure/cosmos-db

Developer

CCRi and others

Machbase

Microsoft

Initial release

2019

2014

2013

2014

Current release

3.4, August 2019

4.0.5, February 2024

V8.0, August 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache License 2.0

commercial

free test version available

commercial

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

Scala

Server operating systems

hosted

FreeBSD
Linux
Windows

experimental

Linux
macOS
Windows

hosted

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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.

Secondary indexes

yes

All properties auto-indexed by default

SQL

Support of SQL

SQL-like query language

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

gRPC
JSON over HTTP

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

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

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Server-side scripts

Stored procedures

JavaScript

Triggers

yes, watching key changes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

none

depending on storage layer

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

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

depending on storage layer

selectable replication factor

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on storage layer

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

Atomic single-document operations

Multi-item ACID transactions with snapshot isolation within a partition

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.

depending on storage layer

yes

volatile and lookup table

User concepts

Access control

Access rights for users and roles

yes

depending on the DBMS used for storage

simple password-based access control

Access rights can be defined down to the item level

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