DBMS > Ehcache vs. Microsoft Azure Cosmos DB vs. PouchDB vs. SwayDB vs. XTDB

System Properties Comparison Ehcache vs. Microsoft Azure Cosmos DB vs. PouchDB vs. SwayDB vs. XTDB

Editorial information provided by DB-Engines

Name

Description

A widely adopted Java cache with tiered storage options

Globally distributed, horizontally scalable, multi-model database service

JavaScript DBMS with an API inspired by CouchDB

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

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

Primary database model

Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Document store

Key-value store

Document store

Secondary database models

Spatial DBMS

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

Score	4.89
Rank	#67	Overall
	#8	Key-value stores

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

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

www.ehcache.org

azure.microsoft.com/services/cosmos-db

pouchdb.com

swaydb.simer.au

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

Technical documentation

www.ehcache.org/documentation

learn.microsoft.com/azure/cosmos-db

pouchdb.com/guides

www.xtdb.com/docs

Developer

Terracotta Inc, owned by Software AG

Microsoft

Apache Software Foundation

Simer Plaha

Juxt Ltd.

Initial release

2009

2014

2012

2018

2019

Current release

3.10.0, March 2022

7.1.1, June 2019

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

commercial

Open Source

GNU Affero GPL V3.0

Open Source

MIT License

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

JavaScript

Scala

Clojure

Server operating systems

All OS with a Java VM

hosted

server-less, requires a JavaScript environment (browser, Node.js)

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

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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

via views

yes

SQL

Support of SQL

SQL-like query language

limited SQL, making use of Apache Calcite

APIs and other access methods

JCache

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

HTTP REST

only for PouchDB Server
JavaScript API

HTTP REST
JDBC

Supported programming languages

Java

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

JavaScript

Java
Kotlin
Scala

Clojure
Java

Server-side scripts

Stored procedures

JavaScript

View functions in JavaScript

Triggers

yes

Cache Event Listeners

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

Sharding

Implicit feature of the cloud service

Sharding

with a proxy-based framework, named couchdb-lounge

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

yes

Implicit feature of the cloud service

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

none

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*

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable Consistency (Strong, Eventual, Weak)

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

supports JTA and can work as an XA resource

Multi-item ACID transactions with snapshot isolation within a partition

Atomic execution of operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

by using IndexedDB, WebSQL or LevelDB as backend

yes

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.

yes

User concepts

Access control

Access rights can be defined down to the item level

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