DBMS > KairosDB vs. Microsoft Azure AI Search vs. Microsoft Azure Cosmos DB vs. Snowflake vs. TerarkDB

System Properties Comparison KairosDB vs. Microsoft Azure AI Search vs. Microsoft Azure Cosmos DB vs. Snowflake vs. TerarkDB

Editorial information provided by DB-Engines

Name

Description

Distributed Time Series DBMS based on Cassandra or H2

Search-as-a-service for web and mobile app development

Globally distributed, horizontally scalable, multi-model database service

Cloud-based data warehousing service for structured and semi-structured data

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Time Series DBMS

Search engine

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Key-value store

Secondary database models

Vector DBMS

Spatial DBMS

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

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Score	5.59
Rank	#63	Overall
	#7	Search engines

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

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

github.com/kairosdb/kairosdb

azure.microsoft.com/en-us/services/search

azure.microsoft.com/services/cosmos-db

www.snowflake.com

github.com/bytedance/terarkdb

Technical documentation

kairosdb.github.io

learn.microsoft.com/en-us/azure/search

learn.microsoft.com/azure/cosmos-db

docs.snowflake.net/manuals/index.html

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Microsoft

Snowflake Computing Inc.

ByteDance, originally Terark

Initial release

2013

2015

2014

2016

Current release

1.2.2, November 2018

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

restricted open source version available

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

C++

Server operating systems

Linux
OS X
Windows

hosted

Data scheme

schema-free

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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

Secondary indexes

yes

All properties auto-indexed by default

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

Graphite protocol
HTTP REST
Telnet API

RESTful HTTP API

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

CLI Client
JDBC
ODBC

C++ API
Java API

Supported programming languages

Java
JavaScript

Node.js
PHP
Python

C#
Java
JavaScript
Python

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

JavaScript (Node.js)
Python

C++
Java

Server-side scripts

Stored procedures

JavaScript

user defined functions

Triggers

JavaScript

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

Implicit feature of the cloud service

Sharding

Implicit feature of the cloud service

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes

Implicit feature of the cloud service

yes

Implicit feature of the cloud service

yes

none

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

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

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

yes

using Azure authentication

Access rights can be defined down to the item level

Users with fine-grained authorization concept, user roles and pluggable authentication

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