DBMS > Hazelcast vs. KairosDB vs. Microsoft Azure Cosmos DB vs. searchxml

System Properties Comparison Hazelcast vs. KairosDB vs. Microsoft Azure Cosmos DB vs. searchxml

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Editorial information provided by DB-Engines

Name

Description

A widely adopted in-memory data grid

Distributed Time Series DBMS based on Cassandra or H2

Globally distributed, horizontally scalable, multi-model database service

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Key-value store

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Native XML DBMS
Search engine

Secondary database models

Document store

JSON support with IMDG 3.12

Spatial DBMS

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

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

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

Score	0.00
Rank	#383	Overall
	#7	Native XML DBMS
	#25	Search engines

Website

hazelcast.com

github.com/kairosdb/kairosdb

azure.microsoft.com/services/cosmos-db

www.searchxml.net/category/products

Technical documentation

hazelcast.org/imdg/docs

kairosdb.github.io

learn.microsoft.com/azure/cosmos-db

www.searchxml.net/support/handouts

Developer

Hazelcast

Microsoft

informationpartners gmbh

Initial release

2008

2013

2014

2015

Current release

5.3.6, November 2023

1.2.2, November 2018

1.0

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache 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

Java

C++

Server operating systems

All OS with a Java VM

Linux
OS X
Windows

hosted

Windows

Data scheme

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.

yes

the object must implement a serialization strategy

yes

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

APIs and other access methods

JCache
JPA
Memcached protocol
RESTful HTTP API

Graphite protocol
HTTP REST
Telnet API

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

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

Java
JavaScript

Node.js
PHP
Python

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

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

JavaScript

yes

on the application server

Triggers

yes

Events

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

selectable replication factor

based on Cassandra

yes

Implicit feature of the cloud service

yes

sychronisation to multiple collections

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

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

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

one or two-phase-commit; repeatable reads; read commited

Multi-item ACID transactions with snapshot isolation within a partition

multiple readers, single writer

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.

yes

User concepts

Access control

Role-based access control

simple password-based access control

Access rights can be defined down to the item level

Domain, group and role-based access control at the document level and for application services

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