DBMS > Blueflood vs. ClickHouse vs. IBM Cloudant vs. Infobright vs. Microsoft Azure Data Explorer

System Properties Comparison Blueflood vs. ClickHouse vs. IBM Cloudant vs. Infobright vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

Database as a Service offering based on Apache CouchDB

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Fully managed big data interactive analytics platform

Primary database model

column oriented

Secondary database models

Time Series DBMS

Document store

If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store

this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine

support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS

see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis

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

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	15.55
Rank	#38	Overall
	#23	Relational DBMS

Score	2.75
Rank	#104	Overall
	#19	Document stores

Score	1.02
Rank	#192	Overall
	#90	Relational DBMS

Score	3.80
Rank	#81	Overall
	#43	Relational DBMS

Website

blueflood.io

clickhouse.com

www.ibm.com/products/cloudant

ignitetech.com/softwarelibrary/infobrightdb

azure.microsoft.com/services/data-explorer

Technical documentation

github.com/rax-maas/blueflood/wiki

clickhouse.com/docs

cloud.ibm.com/docs/Cloudant

docs.microsoft.com/en-us/azure/data-explorer

Developer

Rackspace

Clickhouse Inc.

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Ignite Technologies Inc.; formerly InfoBright Inc.

Microsoft

Initial release

2013

2016

2010

2005

2019

Current release

v24.4.1.2088-stable, May 2024

cloud service with continuous releases

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

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.

DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.
Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.
ClickHouse Cloud: Get the performance you love from open source ClickHouse in a serverless offering that takes care of the details so you can spend more time getting insight out of the fastest database on earth.

Implementation language

Java

C++

Erlang

Server operating systems

Linux
OS X

FreeBSD
Linux
macOS

hosted

Linux
Windows

hosted

Data scheme

predefined scheme

yes

schema-free

yes

Fixed schema with schema-less datatypes (dynamic)

Typing

predefined data types such as float or date

yes

bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-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.

yes

Secondary indexes

yes

Knowledge Grid Technology used instead

all fields are automatically indexed

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

yes

Kusto Query Language (KQL), SQL subset

APIs and other access methods

HTTP REST

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API

Supported programming languages

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

C#
Java
JavaScript
Objective-C
PHP
Ruby

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R

Server-side scripts

Stored procedures

yes

View functions (Map-Reduce) in JavaScript

Yes, possible languages: KQL, Python, R

Triggers

yes

see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

key based and custom

Sharding

none

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

Multi-source replication
Source-replica replication

Source-replica replication

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

yes

Spark connector (open source): github.com/Azure/azure-kusto-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Eventual Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

atomic operations within a document possible

ACID

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

Access rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

Azure Active Directory Authentication

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