DBMS > JaguarDB vs. KairosDB vs. MaxDB vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Table Storage

System Properties Comparison JaguarDB vs. KairosDB vs. MaxDB vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Table Storage

Editorial information provided by DB-Engines

Name

Description

Performant, highly scalable DBMS for AI and IoT applications

Distributed Time Series DBMS based on Cassandra or H2

A robust and reliable RDBMS optimized to run all major SAP solutions

Globally distributed, horizontally scalable, multi-model database service

A Wide Column Store for rapid development using massive semi-structured datasets

Primary database model

Key-value store
Vector DBMS

Time Series DBMS

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Wide column store

Secondary database models

Spatial DBMS

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

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Score	2.32
Rank	#112	Overall
	#55	Relational DBMS

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

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Website

www.jaguardb.com

github.com/kairosdb/kairosdb

maxdb.sap.com

azure.microsoft.com/services/cosmos-db

azure.microsoft.com/en-us/services/storage/tables

Technical documentation

www.jaguardb.com/support.html

kairosdb.github.io

maxdb.sap.com/documentation

learn.microsoft.com/azure/cosmos-db

Developer

DataJaguar, Inc.

SAP, acquired from Software AG (Adabas-D) in 1997

Microsoft

Initial release

2015

2013

1984

2014

2012

Current release

3.3 July 2023

1.2.2, November 2018

7.9.10.12, February 2024

License

Commercial or Open Source

Open Source

GPL V3.0

Open Source

Apache 2.0

commercial

Limited community edition free

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++

the server part. Clients available in other languages

Java

C++

Server operating systems

Linux

Linux
OS X
Windows

AIX
HP-UX
Linux
Solaris
Windows

hosted

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

All properties auto-indexed by default

SQL

Support of SQL

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

SQL-like query language

APIs and other access methods

JDBC
ODBC

Graphite protocol
HTTP REST
Telnet API

ADO.NET
JDBC
ODBC
WebDAV

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

RESTful HTTP API

Supported programming languages

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Java
JavaScript

Node.js
PHP
Python

.Net
C#
Java
Perl
PHP
Python

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

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

JavaScript

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

Sharding

Implicit feature of the cloud service

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

selectable replication factor

based on Cassandra

Source-replica replication

yes

Implicit feature of the cloud service

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

User concepts

Access control

rights management via user accounts

simple password-based access control

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

Access rights based on private key authentication or shared access signatures

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.