DBMS > ClickHouse vs. Infobright vs. Microsoft Azure Synapse Analytics vs. Oracle Coherence vs. Oracle NoSQL

System Properties Comparison ClickHouse vs. Infobright vs. Microsoft Azure Synapse Analytics vs. Oracle Coherence vs. Oracle NoSQL

Editorial information provided by DB-Engines

Name

Description

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.

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

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Oracles in-memory data grid solution

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Primary database model

Relational DBMS

Key-value store

Document store
Key-value store
Relational DBMS

Secondary database models

Time Series DBMS

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

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Website

clickhouse.com

ignitetech.com/softwarelibrary/infobrightdb

azure.microsoft.com/services/synapse-analytics

www.oracle.com/java/coherence

www.oracle.com/database/nosql/technologies/nosql

Technical documentation

clickhouse.com/docs

docs.microsoft.com/azure/synapse-analytics

docs.oracle.com/en/middleware/standalone/coherence

docs.oracle.com/en/database/other-databases/nosql-database/index.html

Developer

Clickhouse Inc.

Ignite Technologies Inc.; formerly InfoBright Inc.

Microsoft

Oracle

Initial release

2016

2005

2016

2007

2011

Current release

v24.4.1.2088-stable, May 2024

14.1, August 2023

23.3, December 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

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

commercial

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

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.

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Implementation language

C++

Java

Server operating systems

FreeBSD
Linux
macOS

Linux
Windows

hosted

All OS with a Java VM

Linux
Solaris SPARC/x86

Data scheme

yes

schema-free

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

Typing

predefined data types such as float or date

yes

optional

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

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

yes

SQL-like DML and DDL statements

APIs and other access methods

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

ADO.NET
JDBC
ODBC

JCache
JPA
RESTful HTTP API

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

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

C#
Java
PHP

.Net
C++
Java

C
C#
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Transact SQL

Triggers

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

key based and custom

none

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

Source-replica replication

yes

yes, with selectable consistency level

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

Transaction concepts

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

ACID

configurable

ACID within a storage node (=shard)

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

yes

In-memory capabilities

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

yes

off heap cache

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.

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

yes

authentification to access the cache via certificates or http basic authentication

Access rights for users and roles

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