DBMS > Coveo vs. Elasticsearch vs. SWC-DB vs. Yanza

System Properties Comparison Coveo vs. Elasticsearch vs. SWC-DB vs. Yanza

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Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

AI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code development

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

A high performance, scalable Wide Column DBMS

Time Series DBMS for IoT Applications

Primary database model

Search engine

Wide column store

Time Series DBMS

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Time Series DBMS

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

Score	2.14
Rank	#116	Overall
	#11	Search engines

Score	128.79
Rank	#8	Overall
	#1	Search engines

Score	0.01
Rank	#378	Overall
	#13	Wide column stores

Website

www.coveo.com

www.elastic.co/elasticsearch

github.com/kashirin-alex/swc-db
www.swcdb.org

yanza.com

Technical documentation

docs.coveo.com

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

Developer

Coveo

Elastic

Alex Kashirin

Yanza

Initial release

2012

2010

2020

2015

Current release

8.6, January 2023

0.5, April 2021

License

Commercial or Open Source

commercial

Open Source

Elastic License

Open Source

GPL V3

commercial

free version available

Cloud-based only

Only available as a cloud service

yes

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C++

Server operating systems

hosted

All OS with a Java VM

Linux

Windows

Data scheme

hybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configuration

schema-free

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

schema-free

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

SQL

Support of SQL

SQL-like query language

APIs and other access methods

RESTful HTTP API

Java API
RESTful HTTP/JSON API

Proprietary protocol
Thrift

HTTP API

Supported programming languages

C#
Java
JavaScript
Python

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

C++

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

Triggers

yes

by using the 'percolation' feature

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

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

yes

Transaction concepts

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

yes

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.

Memcached and Redis integration

User concepts

Access control

granular access controls, API key management, content filters

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More resources

DB-Engines blog posts

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2 January 2018, Paul Andlinger, Matthias Gelbmann

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2 March 2016, Paul Andlinger

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Recent citations in the news

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