DBMS > etcd vs. eXtremeDB vs. Google Cloud Datastore vs. Microsoft Azure Cosmos DB vs. Oracle Coherence

System Properties Comparison etcd vs. eXtremeDB vs. Google Cloud Datastore vs. Microsoft Azure Cosmos DB vs. Oracle Coherence

Editorial information provided by DB-Engines

Name

Description

A distributed reliable key-value store

Natively in-memory DBMS with options for persistency, high-availability and clustering

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

Globally distributed, horizontally scalable, multi-model database service

Oracles in-memory data grid solution

Primary database model

Key-value store

Relational DBMS
Time Series DBMS

Document store

Document store
Graph DBMS
Key-value store
Wide column store

Key-value store

Secondary database models

Spatial DBMS

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

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

Score	0.74
Rank	#223	Overall
	#103	Relational DBMS
	#18	Time Series DBMS

Score	4.47
Rank	#76	Overall
	#12	Document stores

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

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

Website

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

www.mcobject.com

cloud.google.com/datastore

azure.microsoft.com/services/cosmos-db

www.oracle.com/java/coherence

Technical documentation

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

www.mcobject.com/docs/extremedb.htm

cloud.google.com/datastore/docs

learn.microsoft.com/azure/cosmos-db

docs.oracle.com/en/middleware/standalone/coherence

Developer

McObject

Google

Microsoft

Oracle

Initial release

2001

2008

2014

2007

Current release

3.4, August 2019

8.2, 2021

14.1, August 2023

License

Commercial or Open Source

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

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

Implementation language

C and C++

Java

Server operating systems

FreeBSD
Linux
Windows

experimental

AIX
HP-UX
Linux
macOS
Solaris
Windows

hosted

All OS with a Java VM

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, details here

yes

JSON types

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.

support of XML interfaces available

Secondary indexes

yes

All properties auto-indexed by default

SQL

Support of SQL

yes

with the option: eXtremeSQL

SQL-like query language (GQL)

SQL-like query language

APIs and other access methods

gRPC
JSON over HTTP

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

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

JCache
JPA
RESTful HTTP API

Supported programming languages

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

.Net
C
C#
C++
Java
Lua
Python
Scala

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

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

.Net
C++
Java

Server-side scripts

Stored procedures

yes

using Google App Engine

JavaScript

Triggers

yes, watching key changes

yes

by defining events

Callbacks using the Google Apps Engine

JavaScript

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning / sharding

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

Multi-source replication using Paxos

yes

Implicit feature of the cloud service

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

Multi-item ACID transactions with snapshot isolation within a partition

configurable

Concurrency

Support for concurrent manipulation of data

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

yes

Durability

Support for making data persistent

yes

optionally

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Access rights can be defined down to the item level

authentification to access the cache via certificates or http basic authentication

More information provided by the system vendor

Specific characteristics

eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
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Competitive advantages

eXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
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Typical application scenarios

IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
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Key customers

Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
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Market metrics

With hundreds of customers and over 30 million devices/applications using the product...
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Licensing and pricing models

For server use cases, there is a simple per-server license irrespective of the number...
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.