DBMS > ClickHouse vs. Elasticsearch vs. Microsoft Azure Synapse Analytics vs. Oracle Rdb vs. Trafodion

System Properties Comparison ClickHouse vs. Elasticsearch vs. Microsoft Azure Synapse Analytics vs. Oracle Rdb vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

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.

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

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

Transactional SQL-on-Hadoop DBMS

Primary database model

Relational DBMS

Search engine

Relational DBMS

Secondary database models

Time Series DBMS

Document store
Spatial DBMS
Vector DBMS

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

Score	15.55
Rank	#38	Overall
	#23	Relational DBMS

Score	132.83
Rank	#7	Overall
	#1	Search engines

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	1.14
Rank	#178	Overall
	#80	Relational DBMS

Website

clickhouse.com

www.elastic.co/elasticsearch

azure.microsoft.com/services/synapse-analytics

www.oracle.com/database/technologies/related/rdb.html

trafodion.apache.org

Technical documentation

clickhouse.com/docs

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

docs.microsoft.com/azure/synapse-analytics

www.oracle.com/database/technologies/related/rdb-doc.html

trafodion.apache.org/documentation.html

Developer

Clickhouse Inc.

Elastic

Microsoft

Oracle, originally developed by Digital Equipment Corporation (DEC)

Apache Software Foundation, originally developed by HP

Initial release

2016

2010

2016

1984

2014

Current release

v24.4.1.2088-stable, May 2024

8.6, January 2023

7.4.1.1, 2021

2.3.0, February 2019

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Elastic License

commercial

Open Source

Apache 2.0

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

C++

C++, Java

Server operating systems

FreeBSD
Linux
macOS

All OS with a Java VM

hosted

HP Open VMS

Linux

Data scheme

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

yes

Flexible Schema (defined schema, partial schema, schema free)

yes

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

SQL-like query language

yes

APIs and other access methods

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

Java API
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

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
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

C#
Java
PHP

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

yes

Transact SQL

Java Stored Procedures

Triggers

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

key based and custom

Sharding

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.

yes

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Immediate Consistency

Foreign keys

Referential integrity

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

yes

Transaction concepts

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

ACID

yes, on a single node

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

Memcached and Redis integration

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.

yes

fine grained access rights according to SQL-standard

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