DBMS > Apache IoTDB vs. etcd vs. Fauna vs. Immudb vs. Microsoft Azure Cosmos DB

System Properties Comparison Apache IoTDB vs. etcd vs. Fauna vs. Immudb vs. Microsoft Azure Cosmos DB

Editorial information provided by DB-Engines

Name

Description

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

A distributed reliable key-value store

Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.

An open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.

Globally distributed, horizontally scalable, multi-model database service

Primary database model

Time Series DBMS

Key-value store

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Relational DBMS

Spatial DBMS

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

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

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

Score	1.52
Rank	#153	Overall
	#26	Document stores
	#14	Graph DBMS
	#71	Relational DBMS
	#13	Time Series DBMS

Score	0.24
Rank	#305	Overall
	#43	Key-value stores

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

Website

iotdb.apache.org

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

fauna.com

github.com/codenotary/immudb
immudb.io

azure.microsoft.com/services/cosmos-db

Technical documentation

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

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

docs.fauna.com

docs.immudb.io

learn.microsoft.com/azure/cosmos-db

Developer

Apache Software Foundation

Fauna, Inc.

Codenotary

Microsoft

Initial release

2018

2014

2020

2014

Current release

1.1.0, April 2023

3.4, August 2019

1.2.3, April 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Scala

Server operating systems

All OS with a Java VM (>= 1.8)

FreeBSD
Linux
Windows

experimental

hosted

BSD
Linux
macOS
Solaris
Windows
z/OS

hosted

Data scheme

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

SQL-like syntax

SQL-like query language

APIs and other access methods

JDBC
Native API

gRPC
JSON over HTTP

RESTful HTTP API

gRPC protocol
PostgreSQL wire protocol

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

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

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

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

.Net
Go
Java
JavaScript (Node.js)
Python

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

Server-side scripts

Stored procedures

yes

user defined functions

JavaScript

Triggers

yes

yes, watching key changes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

horizontal partitioning

consistent hashing

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

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

Multi-source replication

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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.

yes

User concepts

Access control

yes

Identity management, authentication, and access control

Access rights can be defined down to the item level

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