DBMS > EsgynDB vs. OpenSearch vs. Solr vs. TimescaleDB vs. TinkerGraph

System Properties Comparison EsgynDB vs. OpenSearch vs. Solr vs. TimescaleDB vs. TinkerGraph

Editorial information provided by DB-Engines

Name

Description

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

A distributed, RESTful search and analytics engine forked from Elasticsearch and based on Apache Lucene

A widely used distributed, scalable search engine based on Apache Lucene

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

Secondary database models

Vector DBMS

Spatial DBMS

Relational DBMS

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

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	16.36
Rank	#37	Overall
	#4	Search engines

Score	42.91
Rank	#24	Overall
	#3	Search engines

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Score	0.08
Rank	#348	Overall
	#35	Graph DBMS

Website

www.esgyn.cn

github.com/opensearch-project
opensearch.org

solr.apache.org

www.timescale.com

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

opensearch.org/docs/latest

solr.apache.org/resources.html

docs.timescale.com

Developer

Esgyn

Amazon Web Services

Apache Software Foundation

Timescale

Initial release

2015

2021

2006

2017

2009

Current release

2.5.0, January 2023

9.6.0, April 2024

2.13.0, November 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache Version 2

Open Source

Apache 2.0

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Aiven for OpenSearch: Fully managed open source search and analytics suite. Out-of-the-box integrations get you up and running in a couple of clicks.

Implementation language

C++, Java

Java

Server operating systems

Linux

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Linux
OS X
Windows

Data scheme

yes

schema-free

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

yes

Dynamic Fields enables on-the-fly addition of new fields

yes

schema-free

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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.

yes

Secondary indexes

yes

All search fields are automatically indexed

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

yes

SQL-like query language

Solr Parallel SQL Interface

yes

full PostgreSQL SQL syntax

APIs and other access methods

ADO.NET
JDBC
ODBC

Java API
RESTful HTTP/JSON API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

TinkerPop 3

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Groovy
Java

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Java plugins

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

by using the 'percolation' feature

yes

User configurable commands triggered on index changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes, across time and space (hash partitioning) attributes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

yes

Source-replica replication with hot standby and reads on replicas

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

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

Eventual Consistency

Immediate Consistency

none

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

OpenSearch is a highly scalable and extensible open-source software suite for search,...
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Competitive advantages

Distributed as fully open source under Apache License, Version 2.0 (ALv2), OpenSearch...
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Typical application scenarios

The OpenSearch platform is used across a broad range of search , analytics, and observability...
» more

Licensing and pricing models

The OpenSearch Project offers open source software licensed under Apache License...
» more

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