DBMS > Microsoft Azure Cosmos DB vs. NSDb vs. Postgres-XL vs. SAP Adaptive Server

System Properties Comparison Microsoft Azure Cosmos DB vs. NSDb vs. Postgres-XL vs. SAP Adaptive Server

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Editorial information provided by DB-Engines

Name

Description

Globally distributed, horizontally scalable, multi-model database service

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

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

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

Primary database model

Document store
Graph DBMS
Key-value store
Wide column store

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

Spatial DBMS

with Boeing's Spatial Query Server

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

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	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	35.09
Rank	#25	Overall
	#17	Relational DBMS

Website

azure.microsoft.com/services/cosmos-db

nsdb.io

www.postgres-xl.org

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

Technical documentation

learn.microsoft.com/azure/cosmos-db

nsdb.io/Architecture

www.postgres-xl.org/documentation

help.sap.com/docs/SAP_ASE

Developer

Microsoft

SAP, Sybase

Initial release

2014

2017

2014

since 2012, originally named StormDB

1987

Current release

10 R1, October 2018

16.0

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Mozilla public license

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, Scala

C and C++

Server operating systems

hosted

Linux
macOS

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.

yes

XML type, but no XML query functionality

Secondary indexes

yes

All properties auto-indexed by default

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

distributed, parallel query execution

yes

APIs and other access methods

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

gRPC
HTTP REST
WebSocket

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

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

Supported programming languages

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

Java
Scala

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C
C++
Cobol
Java
Java
Perl
PHP
Python

Server-side scripts

Stored procedures

JavaScript

user defined functions

Java and Transact-SQL

Triggers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

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*

Consistency concepts

Methods to ensure consistency in a distributed system

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

MVCC

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

yes

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

fine grained access rights according to SQL-standard

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