DBMS > Elasticsearch vs. EsgynDB vs. Realm vs. Riak TS vs. Yanza

System Properties Comparison Elasticsearch vs. EsgynDB vs. Realm vs. Riak TS vs. Yanza

Editorial information provided by DB-Engines

Name

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

Description

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

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Time Series DBMS for IoT Applications

Primary database model

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Website

www.elastic.co/elasticsearch

www.esgyn.cn

realm.io

yanza.com

Technical documentation

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

realm.io/docs

www.tiot.jp/riak-docs/riak/ts/latest

Developer

Elastic

Esgyn

Realm, acquired by MongoDB in May 2019

Open Source, formerly Basho Technologies

Yanza

Initial release

2010

2015

2014

2015

Current release

8.6, January 2023

3.0.0, September 2022

License

Commercial or Open Source

Open Source

Elastic License

commercial

Open Source

commercial

free version available

Cloud-based only

Only available as a cloud service

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++, Java

Erlang

Server operating systems

All OS with a Java VM

Linux

Android
Backend: server-less
iOS
Windows

Linux
OS X

Windows

Data scheme

schema-free

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

yes

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

yes

restricted

SQL

Support of SQL

SQL-like query language

yes

yes, limited

APIs and other access methods

Java API
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

HTTP API
Native Erlang Interface

HTTP API

Supported programming languages

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

All languages supporting JDBC/ODBC/ADO.Net

.Net
Java

with Android only
Objective-C
React Native
Swift

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

Java Stored Procedures

runs within the applications so server-side scripts are unnecessary

Erlang

Triggers

yes

by using the 'percolation' feature

yes

Change Listeners

yes

pre-commit hooks and post-commit hooks

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication between multi datacenters

none

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

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

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

Transaction concepts

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

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.

Memcached and Redis integration

yes

In-Memory realm

User concepts

Access control

fine grained access rights according to SQL-standard

yes

More information provided by the system vendor

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Related products and services

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More resources

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