DBMS > Apache Druid vs. Hawkular Metrics vs. IBM Cloudant vs. Microsoft Azure Cosmos DB vs. TerarkDB

System Properties Comparison Apache Druid vs. Hawkular Metrics vs. IBM Cloudant vs. Microsoft Azure Cosmos DB vs. TerarkDB

Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

Database as a Service offering based on Apache CouchDB

Globally distributed, horizontally scalable, multi-model database service

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

Relational DBMS
Time Series DBMS

Time Series DBMS

Document store

Document store
Graph DBMS
Key-value store
Wide column store

Key-value store

Secondary database models

Spatial DBMS

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

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	2.68
Rank	#106	Overall
	#20	Document stores

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
	#60	Key-value stores

Website

druid.apache.org

www.hawkular.org

www.ibm.com/products/cloudant

azure.microsoft.com/services/cosmos-db

github.com/bytedance/terarkdb

Technical documentation

druid.apache.org/docs/latest/design

www.hawkular.org/hawkular-metrics/docs/user-guide

cloud.ibm.com/docs/Cloudant

learn.microsoft.com/azure/cosmos-db

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Apache Software Foundation and contributors

Community supported by Red Hat

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Microsoft

ByteDance, originally Terark

Initial release

2012

2014

2010

2014

2016

Current release

29.0.1, April 2024

License

Commercial or Open Source

Open Source

Apache license v2

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

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Erlang

C++

Server operating systems

Linux
OS X
Unix

Linux
OS X
Windows

hosted

Data scheme

yes

schema-less columns are supported

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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

SQL for querying

SQL-like query language

APIs and other access methods

JDBC
RESTful HTTP/JSON API

HTTP REST

RESTful HTTP/JSON API

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

C++ API
Java API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Go
Java
Python
Ruby

C#
Java
JavaScript
Objective-C
PHP
Ruby

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

C++
Java

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

JavaScript

Triggers

yes

via Hawkular Alerting

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

based on Cassandra

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

selectable replication factor

based on Cassandra

Multi-source replication
Source-replica replication

yes

Implicit feature of the cloud service

none

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

Transaction concepts

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

atomic operations within a document possible

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Access rights for users can be defined per database

Access rights can be defined down to the item level

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.