DBMS > etcd vs. EventStoreDB vs. Microsoft Azure Cosmos DB vs. TerminusDB vs. XTDB

System Properties Comparison etcd vs. EventStoreDB vs. Microsoft Azure Cosmos DB vs. TerminusDB vs. XTDB

Editorial information provided by DB-Engines

Name

Description

A distributed reliable key-value store

Industrial-strength, open-source database solution built from the ground up for event sourcing.

Globally distributed, horizontally scalable, multi-model database service

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Key-value store

Event Store

Document store
Graph DBMS
Key-value store
Wide column store

Graph DBMS

Document store

Secondary database models

Spatial DBMS

Document store
RDF store

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

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

Score	1.19
Rank	#173	Overall
	#1	Event Stores

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

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

www.eventstore.com

azure.microsoft.com/services/cosmos-db

terminusdb.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

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

developers.eventstore.com

learn.microsoft.com/azure/cosmos-db

terminusdb.github.io/terminusdb/#

www.xtdb.com/docs

Developer

Event Store Limited

Microsoft

DataChemist Ltd.

Juxt Ltd.

Initial release

2012

2014

2018

2019

Current release

3.4, August 2019

21.2, February 2021

11.0.0, January 2023

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

commercial

Open Source

GPL V3

Open Source

MIT License

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

Prolog, Rust

Clojure

Server operating systems

FreeBSD
Linux
Windows

experimental

Linux
Windows

hosted

Linux

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

yes

yes, extensible-data-notation format

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

yes

SQL

Support of SQL

SQL-like query language

SQL-like query language (WOQL)

limited SQL, making use of Apache Calcite

APIs and other access methods

gRPC
JSON over HTTP

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

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

HTTP REST
JDBC

Supported programming languages

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

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

JavaScript
Python

Clojure
Java

Server-side scripts

Stored procedures

JavaScript

yes

Triggers

yes, watching key changes

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Graph Partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

Implicit feature of the cloud service

Journaling Streams

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory journaling

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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 can be defined down to the item level

Role-based access control

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