DBMS > AgensGraph vs. ClickHouse vs. Elasticsearch vs. Graph Engine vs. Yaacomo

System Properties Comparison AgensGraph vs. ClickHouse vs. Elasticsearch vs. Graph Engine vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

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

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Graph DBMS
Relational DBMS

Relational DBMS

Search engine

Graph DBMS
Key-value store

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	0.16
Rank	#333	Overall
	#30	Graph DBMS
	#146	Relational DBMS

Score	16.20
Rank	#37	Overall
	#23	Relational DBMS

Score	134.78
Rank	#7	Overall
	#1	Search engines

Score	0.62
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Website

bitnine.net/agensgraph

clickhouse.com

www.elastic.co/elasticsearch

www.graphengine.io

yaacomo.com

Technical documentation

bitnine.net/documentation

clickhouse.com/docs

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

www.graphengine.io/docs/manual

Developer

Bitnine Global Inc.

Clickhouse Inc.

Elastic

Microsoft

Q2WEB GmbH

Initial release

2016

2010

2009

Current release

2.1, December 2018

v24.3.2.23-lts, April 2024

8.6, January 2023

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Apache 2.0

Open Source

Elastic License

Open Source

MIT License

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

.NET and C

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
macOS

All OS with a Java VM

.NET

Android
Linux
Windows

Data scheme

depending on used data model

yes

schema-free

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

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

yes

Close to ANSI SQL (SQL/JSON + extensions)

SQL-like query language

yes

APIs and other access methods

Cypher Query Language
JDBC

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

Java API
RESTful HTTP/JSON API

RESTful HTTP API

JDBC
ODBC

Supported programming languages

C
Java
JavaScript
Python

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#
C++
F#
Visual Basic

Server-side scripts

Stored procedures

yes

Triggers

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

key based and custom

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

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

yes

Source-replica replication

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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

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