DBMS > KairosDB vs. Microsoft Azure Cosmos DB vs. NSDb vs. PouchDB vs. SAP Adaptive Server

System Properties Comparison KairosDB vs. Microsoft Azure Cosmos DB vs. NSDb vs. PouchDB vs. SAP Adaptive Server

Editorial information provided by DB-Engines

Name

Description

Distributed Time Series DBMS based on Cassandra or H2

Globally distributed, horizontally scalable, multi-model database service

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

JavaScript DBMS with an API inspired by CouchDB

The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS

Primary database model

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Time Series DBMS

Document store

Relational DBMS

Secondary database models

Spatial DBMS

with Boeing's Spatial Query Server

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

Score	0.67
Rank	#233	Overall
	#20	Time Series DBMS

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

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	35.09
Rank	#25	Overall
	#17	Relational DBMS

Website

github.com/kairosdb/kairosdb

azure.microsoft.com/services/cosmos-db

nsdb.io

pouchdb.com

www.sap.com/products/technology-platform/sybase-ase.html

Technical documentation

kairosdb.github.io

learn.microsoft.com/azure/cosmos-db

nsdb.io/Architecture

pouchdb.com/guides

help.sap.com/docs/SAP_ASE

Developer

Microsoft

Apache Software Foundation

SAP, Sybase

Initial release

2013

2014

2017

2012

1987

Current release

1.2.2, November 2018

7.1.1, June 2019

16.0

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache Version 2.0

Open Source

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

Java

Java, Scala

JavaScript

C and C++

Server operating systems

Linux
OS X
Windows

hosted

Linux
macOS

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

AIX
HP-UX
Linux
Solaris
Unix
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

yes: int, bigint, decimal, string

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.

Secondary indexes

yes

All properties auto-indexed by default

all fields are automatically indexed

yes

via views

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

Graphite protocol
HTTP REST
Telnet API

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

gRPC
HTTP REST
WebSocket

HTTP REST

only for PouchDB Server
JavaScript API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

Java
JavaScript

Node.js
PHP
Python

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

Java
Scala

JavaScript

C
C++
Cobol
Java
Java
Perl
PHP
Python

Server-side scripts

Stored procedures

JavaScript

View functions in JavaScript

Java and Transact-SQL

Triggers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

Implicit feature of the cloud service

Sharding

with a proxy-based framework, named couchdb-lounge

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes

Implicit feature of the cloud service

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

Multi-source replication
Source-replica replication

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

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

Using Apache Lucene

yes

by using IndexedDB, WebSQL or LevelDB as backend

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

simple password-based access control

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

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